HLA imputation and its application to genetic and molecular fine-mapping of the MHC region in autoimmune diseases

Decoding the genetic comorbidity network of Alzheimer's disease

Alzheimer's disease (AD) has emerged as the most prevalent and complex neurodegenerative disorder among the elderly population. However, the genetic comorbidity etiology for AD remains poorly understood. In this study, we conducted pleiotropic analysis for 41 AD phenotypic comorbidities, identifying ten genetic comorbidities with 16 pleiotropy genes associated with AD. Through biological functional and network analysis, we elucidated the molecular and functional landscape of AD genetic comorbidities. Furthermore, leveraging the pleiotropic genes and reported biomarkers for AD genetic comorbidities, we identified 50 potential biomarkers for AD diagnosis. Our findings deepen the understanding of the occurrence of AD genetic comorbidities and provide new insights for the search for AD diagnostic markers.

Genotype imputation methods for whole and complex genomic regions utilizing deep learning technology

The imputation of unmeasured genotypes is essential in human genetic research, particularly in enhancing the power of genome-wide association studies and conducting subsequent fine-mapping. Recently, several deep learning-based genotype imputation methods for genome-wide variants with the capability of learning complex linkage disequilibrium patterns have been developed. Additionally, deep learning-based imputation has been applied to a distinct genomic region known as the major histocompatibility complex, referred to as HLA imputation. Despite their various advantages, the current deep learning-based genotype imputation methods do have certain limitations and have not yet become standard. These limitations include the modest accuracy improvement over statistical and conventional machine learning-based methods. However, their benefits include other aspects, such as their "reference-free" nature, which ensures complete privacy protection, and their higher computational efficiency. Furthermore, the continuing evolution of deep learning technologies is expected to contribute to further improvements in prediction accuracy and usability in the future.

The Contribution of Genetic and Epigenetic Factors: An Emerging Concept in the Assessment and Prognosis of Inflammatory Bowel Diseases

Inflammatory bowel disease (IBD) represents heterogeneous and relapsing intestinal conditions with a severe impact on the quality of life of individuals and a continuously increasing prevalence. In recent years, the development of sequencing technology has provided new means of exploring the complex pathogenesis of IBD. An ideal solution is represented by the approach of precision medicine that investigates multiple cellular and molecular interactions, which are tools that perform a holistic, systematic, and impartial analysis of the genomic, transcriptomic, proteomic, metabolomic, and microbiomics sets. Hence, it has led to the orientation of current research towards the identification of new biomarkers that could be successfully used in the management of IBD patients. Multi-omics explores the dimension of variation in the characteristics of these diseases, offering the advantage of understanding the cellular and molecular mechanisms that affect intestinal homeostasis for a much better prediction of disease development and choice of treatment. This review focuses on the progress made in the field of prognostic and predictive biomarkers, highlighting the limitations, challenges, and also the opportunities associated with the application of genomics and epigenomics technologies in clinical practice.

Transcriptomic analysis of intestine following administration of a transglutaminase 2 inhibitor to prevent gluten-induced intestinal damage in celiac disease

Transglutaminase 2 (TG2) plays a pivotal role in the pathogenesis of celiac disease (CeD) by deamidating dietary gluten peptides, which facilitates antigenic presentation and a strong anti-gluten T cell response. Here, we elucidate the molecular mechanisms underlying the efficacy of the TG2 inhibitor ZED1227 by performing transcriptional analysis of duodenal biopsies from individuals with CeD on a long-term gluten-free diet before and after a 6-week gluten challenge combined with 100 mg per day ZED1227 or placebo. At the transcriptome level, orally administered ZED1227 effectively prevented gluten-induced intestinal damage and inflammation, providing molecular-level evidence that TG2 inhibition is an effective strategy for treating CeD. ZED1227 treatment preserved transcriptome signatures associated with mucosal morphology, inflammation, cell differentiation and nutrient absorption to the level of the gluten-free diet group. Nearly half of the gluten-induced gene expression changes in CeD were associated with the epithelial interferon-γ response. Moreover, data suggest that deamidated gluten-induced adaptive immunity is a sufficient step to set the stage for CeD pathogenesis. Our results, with the limited sample size, also suggest that individuals with CeD might benefit from an HLA-DQ2/HLA-DQ8 stratification based on gene doses to maximally eliminate the interferon-γ-induced mucosal damage triggered by gluten.

Determination of HLA class II risk alleles and prediction of self/non-self-epitopes contributing Hashimoto's thyroiditis in a group of Iranian patients

One of the probable hypotheses for the onset of autoimmunity is molecular mimicry. This study aimed to determine the HLA-II risk alleles for developing Hashimoto's thyroiditis (HT) in order to analyze the molecular homology between candidate pathogen-derived epitopes and potentially self-antigens (thyroid peroxidase, TPO) based on the presence of HLA risk alleles. HLA-DRB1/-DQB1 genotyping was performed in 100 HT patients and 330 ethnically matched healthy controls to determine the predisposing/protective alleles for HT disease. Then, in silico analysis was conducted to examine the sequence homology between epitopes derived from autoantigens and four potentially relevant pathogens and their binding capacities to HLA risk alleles based on peptide docking analysis. We identified HLA-DRB1*03:01, *04:02, *04:05, and *11:04 as predisposing alleles and DRB1*13:01 as a potentially predictive allele for HT disease. Also, DRB1*11:04 ~ DQB1*03:01 (Pc = 0.002; OR, 3.97) and DRB1*03:01 ~ DQB1*02:01 (Pc = 0.004; OR, 2.24) haplotypes conferred a predisposing role for HT. Based on logistic regression analysis, carrying risk alleles increased the risk of HT development 4.5 times in our population (P = 7.09E-10). Also, ROC curve analysis revealed a high predictive power of those risk alleles for discrimination of the susceptible from healthy individuals (AUC, 0.70; P = 6.6E-10). Analysis of peptide sequence homology between epitopes of TPO and epitopes derived from four candidate microorganisms revealed a homology between envelop glycoprotein D of herpes virus and sequence 151-199 of TPO with remarkable binding capacity to HLA-DRB1*03:01 allele. Our findings indicate the increased risk of developing HT in those individuals carrying HLA risk alleles which can also be related to herpes virus infection.

HLA-DRB5 Overexpression Promotes Platelet Reduction in Immune Thrombocytopenia Mice Model by Facilitating MHC-II-Mediated Antigen Presentation

INTRODUCTION

Major histocompatibility complex II (MHC-II)-mediated antigen presentation contributes to the pathogenesis of immune thrombocytopenia (ITP). Human leukocyte antigen (HLA)-DRB5 is an MHC-II molecule and this study aims to investigate its role and mechanisms in ITP development.

METHODS

Guinea pig anti-mouse platelet (PLT) serum-induced ITP mice received tail vein injection of HLA-DRB5 overexpressing adenoviral vector/immune receptor expressed on myeloid cells-1 (IREM-1) monoclonal antibody (mAb). PLT count changes in mice blood were assessed by a hematology analyzer. MHC-II/CD80/CD86 expression in mice blood was measured by quantitative real-time-PCR and immunofluorescence assay. CD8+ T-cell proportion in mice blood was detected by flow cytometry.

RESULTS

HLA-DRB5 overexpression exacerbated PLT reduction since the 5th day of the establishment of ITP mice model and enhanced MHC-II/CD80/CD86 expression upregulation as well as CD8+ T-cell ratio elevation in the blood of ITP mice, while its effects were reversed by IREM-1 mAb.

CONCLUSION

HLA-DRB5 overexpression upregulates MHC-II-mediated antigen presentation to CD8+ T cells, thus lowering PLT count in the ITP mice model.

Phenomic landscape and pharmacogenomic implications for HLA region in a Taiwan Han Chinese population

BACKGROUND

The human leukocyte antigen (HLA) genes, exhibiting significant genetic diversity, are associated with susceptibility to various clinical diseases and diverse in drug responses. High costs of HLA sequencing and the population-specific architecture of this genetic region necessitate the establishment of a population-specific HLA imputation reference panel. Moreover, there is a lack of understanding about the genetic and phenotypic landscape of HLA variations within the Taiwanese population.

METHODS

We created models for a Taiwanese-specific HLA imputation reference panel. These models were trained with the array genotype data and HLA sequencing data from 845 Taiwanese subjects. HLA imputation was applied for 59,448 Taiwanese subjects to characterize the HLA allele and haplotype frequencies. Additionally, a phenome-wide association study (PheWAS) was conducted to identify the phenotypes associated with HLA variations. The association of the biallelic HLA variants with the binary and quantitative traits were evaluated with additive logistic and linear regression models, respectively. Furthermore, an omnibus test with likelihood-ratio test was applied for each HLA amino acid position in the multiallelic HLA amino acid polymorphisms to compare the difference between a fitted model and a null model following a χ2 distribution of n-1 degree of freedom at a position with n residues. Finally, we estimated the prevalence of adverse drug reactions (ADR)-related HLA alleles in the Taiwanese population.

RESULTS

In this study, the reference panel models displayed remarkable accuracy, with averages of 99.3%, 98.9%, and 99.1% for 2-, 4-, 6-digit alleles of the eight classical HLA genes, respectively. For PheWAS, a total of 18,136 significant associations with HLA variants across 26 phenotypes are identified (p < 5×10-8), highlighting the pleiotropy feature of the HLA region. Among the independent signals, 15 are novel, including the association of HLA-B pos 138 variation with ankylosing spondylitis (AS), and rs9266290 and rs9266292 with allergy. Through an analysis spanning the entire HLA region, we identified clusters of phenotype correlations. Finally, the carriers of pharmacogenomic related HLA alleles, including HLA-C*01:02 (35.86%), HLA-B*58:01 (20.9%), and HLA-B*15:02 (8.38%), were characterized in the Taiwanese general population.

CONCLUSIONS

We successfully delivered the HLA imputation for 59,448 Taiwanese subjects and characterized the genetic and phenotypic landscapes of the HLA variations. In addition, we quantified the estimated prevalence of the ADR-related HLA alleles in the Taiwanese population. The developed HLA imputation reference panel could be used for estimation of population HLA allele frequencies, which can facilitate further studies in the role of HLA variants in a wider range of phenotypes in the population.

Family-based association of HLA-DRB1 and DQB1 alleles and haplotypes in a group of Iranian Type 1 diabetes children

This family-based study was conducted in a group of Iranians with Type 1 diabetes (T1D) to investigate the transmission from parents of risk and non-risk HLA alleles and haplotypes, and to estimate the genetic risk score for this disease within this population. A total of 240 T1D subjects including 111 parent-child trios (111 children with T1D, 133 siblings, and 222 parents) and 330 ethnically matched healthy individuals were recruited. High-resolution HLA typing for DRB1/DQB1 loci was performed for all study subjects (n = 925) using polymerase chain reaction-sequence-specific oligonucleotide probe method. The highest predisposing effect on developing T1D was conferred by the following haplotypes both in all subjects and in probands compared to controls: DRB1*04:05-DQB1*03:02 (Pc = 2.97e-06 and Pc = 6.04e-10, respectively), DRB1*04:02-DQB1*03:02 (Pc = 5.94e-17 and Pc = 3.86e-09, respectively), and DRB1*03:01-DQB1*02:01 (Pc = 8.26e-29 and Pc = 6.56e-16, respectively). Conversely, the major protective haplotypes included DRB1*13:01-DQB1*06:03 (Pc = 6.99e-08), DRB1*15:01-DQB1*06:02 (Pc = 2.97e-06) in the cases versus controls. Also, DRB1*03:01-DQB1*02:01/DRB1*04:02|05-DQB1*03:02 and DRB1*03:01-DQB1*02:01/DRB1*03:01-DQB1*02:01 diplotypes conferred the highest predisposing effect in the cases (Pc = 8.65e-17 and Pc = 6.26e-08, respectively) and in probands (Pc = 5.4e-15 and Pc = 0.001, respectively) compared to controls. Transmission disequilibrium test showed that the highest risk was conferred by DRB1*04:02-DQB1*03:02 (Pc = 3.26e-05) and DRB1*03:01-DQB1*02:01 (Pc = 1.78e-12) haplotypes and the highest protection by DRB1*14:01-DQB1*05:03 (Pc = 8.66e-05), DRB1*15:01-DQB1*06:02 (Pc = 0.002), and DRB1*11:01-DQB1*03:01 (Pc = 0.0003) haplotypes. Based on logistic regression analysis, carriage of risk haplotypes increased the risk of T1D development 24.5 times in the Iranian population (p = 5.61e-13). Also, receiver operating characteristic curve analysis revealed a high predictive power of those risk haplotypes in discrimination of susceptible from healthy individuals (area under curve: 0.88, p = 5.5e-32). Our study highlights the potential utility of genetic risk assessment based on HLA diplotypes for predicting T1D risk in individuals, particularly among family members of affected children in our population.

An Autopsy-proven Case-based Review of Autoimmune Encephalitis

Autoimmune encephalitis (AIE) is a type of immunoreactive encephalitic disorder and is recognized as the most prevalent noninfectious encephalitis. Nevertheless, the rarity of definitive AIE diagnosis through biopsy or autopsy represents a significant hurdle to understanding and managing the disease. In this article, we present the pathological findings of AIE and review the literature based on a distinct case of AIE presenting as CD8+ T-lymphocyte predominant encephalitis. We describe the clinical progression, diagnostic imaging, laboratory data, and autopsy findings of an 80-year-old deceased male patient. The patient was diagnosed with pulmonary tuberculosis 6 months before death and received appropriate medications. A week before admission to the hospital, the patient manifested symptoms such as a tendency to sleep, decreased appetite, and confusion. Although the patient temporally improved with medication including correction of hyponatremia, the patient progressed rapidly and died in 6 weeks. The brain tissue revealed lymphocytic infiltration in the gray and white matter, leptomeninges, and perivascular infiltration with a predominance of CD8+ T lymphocytes, suggesting a case of AIE. There was no detectable evidence of viral infection or underlying neoplasm. The autopsy revealed that this patient also had Alzheimer's disease, atherosclerosis, arteriolosclerosis, and aging-related tau astrogliopathy. This report emphasizes the pivotal role of pathological examination in the diagnosis of AIE, especially when serological autoantibody testing is not available or when a patient is suspected of having multiple diseases.

Deep Learning-Based HLA Allele Imputation Applicable to GWAS

Human leukocyte antigen (HLA) imputation is an essential step following genome-wide association study, particularly when putative associations in HLA genes are identified, to fully understand the genetic basis of human traits. Different HLA imputation methods have been developed, each with its own advantages, and recent methods have been improved in terms of imputation accuracy and computational costs. Here, I describe Deep*HLA, a recently published method that employs deep learning algorithms to accurately impute HLA alleles from regional single nucleotide variants. Deep*HLA was trained and benchmarked on two reference panels of different ancestries. Deep*HLA achieved high imputation accuracy with relatively mild reduced imputation accuracy for rare alleles. I provide a detailed protocol for running Deep*HLA, including instructions for data preprocessing, model training, and imputation. Deep*HLA is implemented in Python 3 and is freely available.

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.

The latest breakthrough on genetic characteristics of inflammatory bowel disease in Chinese and other East Asian ancestries

Inflammatory bowel diseases (IBDs) are complex chronic disorders of the gastrointestinal tract with the following two subtypes: Crohn's disease and ulcerative colitis. Disease presentation and progression within and across IBDs, especially Crohn's disease, are highly heterogeneous in the location, severity of inflammation, intestinal stenosis and obstruction, and extraintestinal manifestations. Clinical classifications fail to accurately predict the disease course and response to therapies. To date, most IBD genetic associations are derived from individuals of European ancestries, leading to a limitation of the discovery and application of IBD genetics in the rest of the world populations. In this mini-review, we summarize the latest progress of genome-wide association studies of IBD across global ancestries especially the Chinese population, the similarities and differences in genetic architecture between European and East Asian ancestries, as well as, the clinical significances relevant to IBD genetic study.

Nrf2 regulates the activation of THP-1 cells induced by chloral hydrate

Trichloroethylene (TCE) triggers a severe hypersensitivity syndrome in the occupational population dependent on dendritic cells (DCs). Chloral hydrate (CH), the major oxidative metabolite of TCE, has been proved to be the culprit causative substance of TCE-induced hypersensitivity by human patch tests. Because redox imbalance is essential for chemical sensitizers-induced maturation of DCs, we predicted that CH would activate DCs by the nuclear factor E2-related factor 2 (Nrf2)-mediated antioxidant response. This study selected THP-1 cells as the in vitro DC model, and we evaluated the cell activation markers, intracellular oxidative stress, and Nrf2 pathway related genes expression in response to CH in THP-1 cells. CH displayed significant stimulation of THP-1 cells activation, including CD54 and CD86 expression, IL-8 release, and cell migration, and damaged the redox balance by triggering ROS generation, GSH consumption, and antioxidase activities modulation. The levels of Nrf2 and its downstream genes (HO-1 and NQO1) in mRNA and protein expressions were upregulated by CH, and CH also promoted the nuclear translocation of Nrf2. Subsequently, we investigated the effects of antioxidant on Nrf2-mediated cell defense in CH treated cells. Pretreatment with curcumin dramatically reduced cell activation and oxidative stress triggered by CH in THP-1 cells. We also confirmed the specific role of Nrf2 in CH-induced cell activation using NRF2-knockout cells. Deficiency of Nrf2 inhibited cell activation and downregulated HO-1 and NQO1 expression in CH-challenged cells. These findings suggest that Nrf2-dependent redox homeostasis plays a pivotal role in CH-induced activation of THP-1 cells, thereby providing new knowledge of the allergen as well as the molecular mechanism involving in TCE-induce hypersensitivity syndrome.

Exploring the causal role of the immune response to varicella-zoster virus on multiple traits: a phenome-wide Mendelian randomization study

BACKGROUND

The immune response to infections could be largely driven by the individual's genes, especially in the major histocompatibility complex (MHC) region. Varicella-zoster virus (VZV) is a highly communicable pathogen. In addition to infection, the reactivations of VZV can be a potential causal factor for multiple traits. Identification of VZV immune response-related health conditions can therefore help elucidate the aetiology of certain diseases.

METHODS

A phenome-wide Mendelian randomization (MR) study of anti-VZV immunoglobulin G (IgG) levels with 1370 traits was conducted to explore the potential causal role of VZV-specific immune response on multiple traits using the UK Biobank cohort. For the robustness of the results, we performed MR analyses using five different methods. To investigate the impact of the MHC region on MR results, the analyses were conducted using instrumental variables (IVs) inside (IV_mhc) and outside (IV_no.mhc) the MHC region or all together (IV_full).

RESULTS

Forty-nine single nucleotide polymorphisms (IV_full) were associated with anti-VZV IgG levels, of which five (IV_mhc) were located in the MHC region and 44 (IV_no.mhc) were not. Statistical evidence (false discovery rate < 0.05 in at least three of the five MR methods) for a causal effect of anti-VZV IgG levels was found on 22 traits using IV_mhc, while no evidence was found when using IV_no.mhc or IV_full. The reactivations of VZV increased the risk of Dupuytren disease, mononeuropathies of the upper limb, sarcoidosis, coeliac disease, teeth problems and earlier onset of allergic rhinitis, which evidence was concordant with the literature. Suggestive causal evidence (P < 0.05 in at least three of five MR methods) using IV_full, IV_mhc and IV_no.mhc was detected in 92, 194 and 56 traits, respectively. MR results from IV_full correlated with those from IV_mhc or IV_no.mhc. However, the results between IV_mhc and IV_no.mhc were noticeably different, as evidenced by causal associations in opposite directions between anti-VZV IgG and ten traits.

CONCLUSIONS

In this exploratory study, anti-VZV IgG was causally associated with multiple traits. IVs in the MHC region might have a substantial impact on MR, and therefore, could be potentially considered in future MR studies.

Targeted capture enrichment and sequencing identifies HLA variants associated with the severity of COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19) is currently a global pandemic. The pathogenesis of severe COVID-19 has been widely investigated, but it is still unclear. Human leukocyte antigen (HLA) plays a central role in immune response, and its variants might be related to COVID-19 progression and severity.

OBJECTIVE

To investigate the hypothesis that individual HLA variations could alter the course of COVID-19 and might be associated with the severity of COVID-19.

METHODS

In this study, we conducted an HLA targeted capture enrichment and sequencing of severe COVID-19 patients matched to mild cases. A total of 16 COVID-19 patients, confirmed by SARS-CoV-2 viral RNA polymerase-chain-reaction (PCR) test and chest computed tomography (CT) scan, were enrolled in this study. The HLA targeted capture enrichment and sequencing were conducted. HLA typing was performed by comparing contigs with IPD-IMGT/HLA Database.

RESULTS

In this study, 139 four-digit resolution HLA alleles were acquired. The results showed that HLA-DRB3*01:01 allele was significantly associated with the severity of COVID-19 (odds ratio [OR] = 27.64, 95% confidence interval [CI] = 1.35-560.50, P = 0.0064). And HLA-K*01:01 might be a potential risk factor for COVID-19 severity (OR = 0.11, 95% CI = 0.017-0.66, P = 0.019), but HLA-K*01:02 might be a protective factor (OR = 7.50, 95% CI = 1.48-37.92, P = 0.019).

CONCLUSION

Three non-classical HLA alleles, including HLA-DRB3*01:01, HLA-K*01:01, HLA-K*01:02 were identified to be associated with the severity of COVID-19 by comparing mild and severe patients. The current findings would be helpful for exploring the influence of HLA gene polymorphisms on the development and severity of COVID-19.

Distributions of the HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 alleles and haplotype frequencies of 1763 stem cell donors in the Colombian Bone Marrow Registry typed by next-generation sequencing

The HLA compatibility continues to be the main limitation when finding compatible donors, especially if an identical match is not found within the patient's family group. The creation of bone marrow registries allowed a therapeutic option by identifying 10/10 compatible unrelated donors (URD). However, the availability and frequency of haplotypes and HLA alleles are different among ethnic groups and geographical areas, increasing the difficulty of finding identical matches in international registries. In this study, the HLA-A, -B, -C, -DRB1, and -DQB1 loci of 1763 donors registered in the Colombian Bone Marrow Registry were typed by next-generation sequencing. A total of 52 HLA-A, 111 HLA-B, 41 HLA-C, 47 HLA-DRB1, and 20 HLA-DQB1 alleles were identified. The 3 most frequent alleles for each loci were A*24:02g (20,8%), A*02:01g (16,1%), A*01:01g (7.06%); B*35:43g (7.69%), B*40:02g (7.18%), B*44:03g (6.07%); C*04:01g (15.40%), C*01:02g (10.49%), C*07:02g (10.44%); DRB1*04:07g (11.03%), DRB1*07:01g (9.78%), DRB1*08:02g (6.72%); DQB1*03:02g (20.96%), DQB1*03:01g (17.78%) and DQB1*02:01g (16.05%). A total of 497 HLA-A-C-B-DRB1-DQB1 haplotypes were observed with a frequency greater than or equal to 0.05% (> 0.05%); the haplotypes with the highest frequency were A*24:02g~B*35:43g~C*01:02g~DQB1*03:02g~DRB1*04:07g (3.34%), A*29:02g~B*44:03g~C*16:01g~DQB1*02:01g~DRB1*07:01g (2.04%), and A*01:01g~B*08:01g~C*07:01g~DQB1*02:01g~DRB1*03:01g (1.83%). This data will allow the new Colombian Bone Marrow Donor Registry to assess the genetic heterogeneity of the Colombian population and serve as a tool of interest for future searches of unrelated donors in the country.

Liquid Biopsy, a Potential New Detection Method in Heart Allograft Rejection

Allografts rejection remains the most important reason causing allograft dysfunction in heart transplantation recipients. Currently, the golden standard for detecting graft rejection is endomyocardial biopsy (EMB). As a new noninvasive technique, liquid biopsy emerges along with the great developments of droplet-based digital PCR and the various optimizations of next-generation sequencing technologies, which is also cheaper than EMB. This review introduces several types of liquid biopsy and its application in heart transplantation.

How genetic risk contributes to autoimmune liver disease

Genome-wide association studies (GWAS) for autoimmune hepatitis (AIH) and GWAS/genome-wide meta-analyses (GWMA) for primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) have been successful over the past decade, identifying about 100 susceptibility loci in the human genome, with strong associations with the HLA locus and many susceptibility variants outside the HLA locus with relatively low risk. However, identifying causative variants and genes and determining their effects on liver cells and their immunological microenvironment is far from trivial. Polygenic risk scores (PRSs) based on current genome-wide data have limited potential to predict individual disease risk. Interestingly, results of mediated expression score regression analysis provide evidence that a substantial portion of gene expression at susceptibility loci is mediated by genetic risk variants, in contrast to many other complex diseases. Genome- and transcriptome-wide comparisons between AIH, PBC, and PSC could help to better delineate the shared inherited component of autoimmune liver diseases (AILDs), and statistical fine-mapping, chromosome X-wide association testing, and genome-wide in silico drug screening approaches recently applied to GWMA data from PBC could potentially be successfully applied to AIH and PSC. Initial successes through single-cell RNA sequencing (scRNA-seq) experiments in PBC and PSC now raise high hopes for understanding the impact of genetic risk variants in the context of liver-resident immune cells and liver cell subpopulations, and for bridging the gap between genetics and disease.