Polygenic burdens on cell-specific pathways underlie the risk of rheumatoid arthritis

Genome-wide association study of epilepsy in a Japanese population identified an associated region at chromosome 12q24

OBJECTIVE

Although a number of genes responsible for epilepsy have been identified through Mendelian genetic approaches, and genome-wide association studies (GWASs) have implicated several susceptibility loci, the role of ethnic-specific markers remains to be fully explored. We aimed to identify novel genetic associations with epilepsy in a Japanese population.

METHODS

We conducted a GWAS on 1825 patients with a variety of epilepsies and 7975 control individuals. Expression quantitative trait locus (eQTL) analysis of epilepsy-associated single nucleotide polymorphisms (SNPs) was performed using Japanese eQTL data.

RESULTS

We identified a novel region, which is ~2 Mb (lead SNP rs149212747, p = 8.57 × 10^-10 ), at chromosome 12q24 as a risk for epilepsy. Most of these loci were polymorphic in East Asian populations including Japanese, but monomorphic in the European population. This region harbors 24 transcripts including genes expressed in the brain such as CUX2, ATXN2, BRAP, ALDH2, ERP29, TRAFD1, HECTD4, RPL6, PTPN11, and RPH3A. The eQTL analysis revealed that the associated SNPs are also correlated to differential expression of genes at 12q24.

SIGNIFICANCE

These findings suggest that a gene or genes in the CUX2-RPH3A ~2-Mb region contribute to the pathology of epilepsy in the Japanese population.

Progress in Defining the Genetic Contribution to Type 2 Diabetes in Individuals of East Asian Ancestry

PURPOSE OF REVIEW

Prevalence of type 2 diabetes (T2D) and progression of complications differ between worldwide populations. While obesity is a major contributing risk factor, variations in physiological manifestations, e.g., developing T2D at lower body mass index in some populations, suggest other contributing factors. Early T2D genetic associations were mostly discovered in European ancestry populations. This review describes the progression of genetic discoveries associated with T2D in individuals of East Asian ancestry in the last 10 years and highlights the shared genetic susceptibility between the population groups and additional insights into genetic contributions to T2D.

RECENT FINDINGS

Through increased sample size and power, new genetic associations with T2D were discovered in East Asian ancestry populations, often with higher allele frequencies than European ancestry populations. As we continue to generate maps of T2D-associated variants across diverse populations, there will be a critical need to expand and diversify other omics resources to enable integration for clinical translation.

Whole-organism eQTL mapping at cellular resolution with single-cell sequencing

Genetic regulation of gene expression underlies variation in disease risk and other complex traits. The effect of expression quantitative trait loci (eQTLs) varies across cell types; however, the complexity of mammalian tissues makes studying cell-type eQTLs highly challenging. We developed a novel approach in the model nematode Caenorhabditis elegans that uses single-cell RNA sequencing to map eQTLs at cellular resolution in a single one-pot experiment. We mapped eQTLs across cell types in an extremely large population of genetically distinct C. elegans individuals. We found cell-type-specific trans eQTL hotspots that affect the expression of core pathways in the relevant cell types. Finally, we found single-cell-specific eQTL effects in the nervous system, including an eQTL with opposite effects in two individual neurons. Our results show that eQTL effects can be specific down to the level of single cells.

Genomics-driven drug discovery based on disease-susceptibility genes

Genome-wide association studies have identified numerous disease-susceptibility genes. As knowledge of gene–disease associations accumulates, it is becoming increasingly important to translate this knowledge into clinical practice. This challenge involves finding effective drug targets and estimating their potential side effects, which often results in failure of promising clinical trials. Here, we review recent advances and future perspectives in genetics-led drug discovery, with a focus on drug repurposing, Mendelian randomization, and the use of multifaceted omics data.

rs1944919 on chromosome 11q23.1 and its effector genes COLCA1/COLCA2 confer susceptibility to primary biliary cholangitis

Primary biliary cholangitis (PBC) is a chronic, progressive cholestatic liver disease in which intrahepatic bile ducts are destroyed by an autoimmune reaction. Our previous genome-wide association study (GWAS) identified chromosome 11q23.1 as a susceptibility gene locus for PBC in the Japanese population. Here, high-density association mapping based on single nucleotide polymorphism (SNP) imputation and in silico/in vitro functional analyses identified rs1944919 as the primary functional variant. Expression-quantitative trait loci analyses showed that the PBC susceptibility allele of rs1944919 was significantly associated with increased COLCA1/COLCA2 expression levels. Additionally, the effects of rs1944919 on COLCA1/COLCA2 expression levels were confirmed using genotype knock-in versions of cell lines constructed using the CRISPR/Cas9 system and differed between rs1944919-G/G clones and -T/T clones. To our knowledge, this is the first study to demonstrate the contribution of COLCA1/COLCA2 to PBC susceptibility.

Elucidation of disease etiology by trans-layer omics analysis

To date, genome-wide association studies (GWASs) have successfully identified thousands of associations between genetic polymorphisms and human traits. However, the pathways between the associated genotype and phenotype are often poorly understood. The transcriptome, proteome, and metabolome, the omics, are positioned along the pathway and can provide useful information to translate from genotype to phenotype. This review shows useful data resources for connecting each omics and describes how they are combined into a cohesive analysis. Quantitative trait loci (QTL) are useful information for connecting the genome and other omics. QTL represent how much genetic variants have effects on other omics and give us clues to how GWAS risk SNPs affect biological mechanisms. Integration of each omics provides a robust analytical framework for estimating disease causality, discovering drug targets, and identifying disease-associated tissues. Technological advances and the rise of consortia and biobanks have facilitated the analyses of unprecedented data, improving both the quality and quantity of research. Proficient management of these valuable datasets allows discovering novel insights into the genetic background and etiology of complex human diseases and contributing to personalized medicine.

Genetic variants shape rheumatoid arthritis-specific transcriptomic features in CD4+ T cells through differential DNA methylation, explaining a substantial proportion of heritability

OBJECTIVE

CD4⁺ T cells have been suggested as the most disease-relevant cell type in rheumatoid arthritis (RA) in which RA-risk non-coding variants exhibit allele-specific effects on regulation of RA-driving genes. This study aimed to understand RA-specific signatures in CD4⁺ T cells using multi-omics data, interpreting inter-omics relationships in shaping the RA transcriptomic landscape.

METHODS

We profiled genome-wide variants, gene expression and DNA methylation in CD4⁺ T cells from 82 patients with RA and 40 healthy controls using high-throughput technologies. We investigated differentially expressed genes (DEGs) and differential methylated regions (DMRs) in RA and localised quantitative trait loci (QTLs) for expression and methylation. We then integrated these based on individual-level correlations to inspect DEG-regulating sources and investigated the potential regulatory roles of RA-risk variants by a partitioned-heritability enrichment analysis with RA genome-wide association summary statistics.

RESULTS

A large number of RA-specific DEGs were identified (n=2575), highlighting T cell differentiation and activation pathways. RA-specific DMRs, preferentially located in T cell regulatory regions, were correlated with the expression levels of 548 DEGs mostly in the same topologically associating domains. In addition, expressional variances in 771 and 83 DEGs were partially explained by expression QTLs for DEGs and methylation QTLs (meQTLs) for DEG-correlated DMRs, respectively. A large number of RA variants were moderately to strongly correlated with meQTLs. DEG-correlated DMRs, enriched with meQTLs, had strongly enriched heritability of RA.

CONCLUSION

Our findings revealed that the methylomic changes, driven by RA heritability-explaining variants, shape the differential expression of a substantial fraction of DEGs in CD4⁺ T cells in patients with RA, reinforcing the importance of a multidimensional approach in disease-relevant tissues.

Functional genomics of autoimmune diseases

For more than a decade, genome-wide association studies have been applied to autoimmune diseases and have expanded our understanding on the pathogeneses. Genetic risk factors associated with diseases and traits are essentially causative. However, elucidation of the biological mechanism of disease from genetic factors is challenging. In fact, it is difficult to identify the causal variant among multiple variants located on the same haplotype or linkage disequilibrium block and thus the responsible biological genes remain elusive. Recently, multiple studies have revealed that the majority of risk variants locate in the non-coding region of the genome and they are the most likely to regulate gene expression such as quantitative trait loci. Enhancer, promoter and long non-coding RNA appear to be the main target mechanisms of the risk variants. In this review, we discuss functional genetics to challenge these puzzles.

Epigenetic fine-mapping: identification of causal mechanisms for autoimmunity

Genome-wide association studies (GWAS) have identified genetic susceptibility loci for a variety of autoimmune and inflammatory diseases. These studies confirm the fundamental genetic basis of individual autoimmune diseases, and also point to shared etiological mechanisms across the spectrum of autoimmunity. While hundreds of genetic loci have been implicated in autoimmune diseases, the translation of individual susceptibility loci into specific molecular mechanisms for individual diseases remains difficult. This review highlights recent advances in the genetics of autoimmune disease, and the emerging use of epigenetic techniques to identify pathogenic cell types and causal molecular mechanisms of autoimmunity.

Multi-omics study for interpretation of genome-wide association study

Genome-wide association studies (GWASs) have identified thousands of genetic loci associated with complex traits, including a wide variety of diseases. Despite the successful identification of associated loci, interpreting GWAS findings remains challenging and requires other biological resources. Omics, including genomics, transcriptomics, proteomics, metabolomics, and epigenomics, are increasingly used in a broad range of research fields. Integrative analyses applying GWAS with these omics data are expected to expand our knowledge of complex traits and provide insight into the pathogenesis of complex diseases and their causative factors. Recently, associations between genetic variants and omics data have been comprehensively evaluated, providing new information on the influence of genetic variants on omics. Furthermore, recent advances in analytic methods, including single-cell technologies, have revealed previously unknown disease mechanisms. To advance our understanding of complex traits, integrative analysis using GWAS with multi-omics data is needed. In this review, I describe successful examples of integrative analyses based on omics and GWAS, discuss the limitations of current multi-omics analyses, and provide a perspective on future integrative studies.

Uromodulin (Tamm-Horsfall protein): guardian of urinary and systemic homeostasis

Biology has taught us that a protein as abundantly made and conserved among species as Tamm-Horsfall protein (THP or uromodulin) cannot just be a waste product serving no particular purpose. However, for many researchers, THP is merely a nuisance during urine proteome profiling or exosome purification and for clinicians an enigmatic entity without clear disease implications. Thanks to recent human genetic and correlative studies and animal modeling, we now have a renewed appreciation of this highly prevalent protein in not only guarding urinary homeostasis, but also serving as a critical mediator in systemic inter-organ signaling. Beyond a mere barrier that lines the tubules, or a surrogate for nephron mass, mounting evidence suggests that THP is a multifunctional protein critical for modulating renal ion channel activity, salt/water balance, renal and systemic inflammatory response, intertubular communication, mineral crystallization and bacterial adhesion. Indeed, mutations in THP cause a group of inherited kidney diseases, and altered THP expression is associated with increased risks of urinary tract infection, kidney stone, hypertension, hyperuricemia and acute and chronic kidney diseases. Despite the recent surge of information surrounding THP's physiological functions and disease involvement, our knowledge remains incomplete regarding how THP is normally regulated by external and intrinsic factors, how precisely THP deficiency leads to urinary and systemic pathophysiology and in what clinical settings THP can be used as a theranostic biomarker and a target for modulation to improve patient outcomes.

Linking of genetic risk variants to disease-specific gene expression via multi-omics studies in rheumatoid arthritis

Rheumatoid arthritis (RA) is an autoimmune disease of unknown pathologic mechanism. Extensive single-level analyses have been conducted, including genome-wide association studies (GWASs) and genome-wide copy number variation analyses, whole transcriptomics, and epigenetic analyses. These data are analyzed separately to identify RA-associated genetic components. Recently, it has become possible to integrate these analyses, as multi-omics studies, to obtain more accurate results to infer novel insights into disease causality. GWASs have enabled us to understand RA causal risks, but how these risks are functionally related to RA remains unclear. To date, more than 100 loci have been associated with RA, and 80% of these risk variants are located in non-coding regions. This suggests that polygenic diseases such as RA are likely to be substantiated by changes in the RNA expression of responsible genes, rather than structural or functional changes in proteins. These genetic variants would also affect promoter and enhancer activity, alternative splicing, chromatin configuration, and mRNA stability. Loci identified by GWASs that have no apparent connection to each other may also be controlled by common transcription factors. Statistical approaches such as gene enrichment analysis and polygenic analysis may clarify the key genetic contribution that cannot be identified by GWAS significant signals. These approaches could also clarify many of the missing links between genetic risk variants and causal genetic components, thus expanding our understanding of RA pathogenesis.

Common genetic susceptibility loci link PFAPA syndrome, Behçet's disease, and recurrent aphthous stomatitis

Periodic fever, aphthous stomatitis, pharyngitis, and cervical adenitis (PFAPA) syndrome is the most common periodic fever syndrome in children. The disease appears to cluster in families, but the pathogenesis is unknown. We queried two European-American cohorts and one Turkish cohort (total n = 231) of individuals with PFAPA for common variants previously associated with two other oropharyngeal ulcerative disorders, Behçet's disease and recurrent aphthous stomatitis. In a metaanalysis, we found that a variant upstream of IL12A (rs17753641) is strongly associated with PFAPA (OR 2.13, P = 6 × 10-9). We demonstrated that monocytes from individuals who are heterozygous or homozygous for this risk allele produce significantly higher levels of IL-12p70 upon IFN-γ and LPS stimulation than those from individuals without the risk allele. We also found that variants near STAT4, IL10, and CCR1-CCR3 were significant susceptibility loci for PFAPA, suggesting that the pathogenesis of PFAPA involves abnormal antigen-presenting cell function and T cell activity and polarization, thereby implicating both innate and adaptive immune responses at the oropharyngeal mucosa. Our results illustrate genetic similarities among recurrent aphthous stomatitis, PFAPA, and Behçet's disease, placing these disorders on a common spectrum, with recurrent aphthous stomatitis on the mild end, Behçet's disease on the severe end, and PFAPA intermediate. We propose naming these disorders Behçet's spectrum disorders to highlight their relationship. HLA alleles may be factors that influence phenotypes along this spectrum as we found new class I and II HLA associations for PFAPA distinct from Behçet's disease and recurrent aphthous stomatitis.

Review: transcriptome and trans-omics analysis of systemic lupus erythematosus

Systemic lupus erythematosus (SLE), which was recognized as a defined clinical entity more than 100 years ago, is an archetype for systemic autoimmune diseases. The 10-year survival of SLE patients has shown dramatic improvement during the last half-century. However, SLE patients receiving long-term prednisone therapy are at high risk of morbidity due to organ damage. Identification of key immune pathways is mandatory to develop a suitable therapy and to stratify patients based on their responses to therapy. Recently developed transcriptome and omic analyses have revealed a number of immune pathways associated with systemic autoimmunity. In addition to type I interferon, plasmablast and neutrophil signatures demonstrate associations with the SLE phenotype. Systematic investigations of these findings enable us to understand and stratify SLE according to the clinical and immunological features.

Transethnic Meta-Analysis of Genome-Wide Association Studies Identifies Three New Loci and Characterizes Population-Specific Differences for Coronary Artery Disease

BACKGROUND

Genome-wide association studies provided many biological insights into coronary artery disease (CAD), but these studies were mainly performed in Europeans. Genome-wide association studies in diverse populations have the potential to advance our understanding of CAD.

METHODS

We conducted 2 genome-wide association studies for CAD in the Japanese population, which included 12 494 cases and 28 879 controls and 2808 cases and 7261 controls, respectively. Then, we performed transethnic meta-analysis using the results of the coronary artery disease genome-wide replication and meta-analysis plus the coronary artery disease 1000 Genomes meta-analysis with UK Biobank. We then explored the pathophysiological significance of these novel loci and examined the differences in CAD-susceptibility loci between Japanese and Europeans.

RESULTS

We identified 3 new loci on chromosome 1q21 (CTSS), 10q26 (WDR11-FGFR2), and 11q22 (RDX-FDX1). Quantitative trait locus analyses suggested the association of CTSS and RDX-FDX1 with atherosclerotic immune cells. Tissue/cell type enrichment analysis showed the involvement of arteries, adrenal glands, and fat tissues in the development of CAD. We next compared the odds ratios of lead variants for myocardial infarction at 76 genome-wide significant loci in the transethnic meta-analysis and a moderate correlation between Japanese and Europeans, where 8 loci showed a difference. Finally, we performed tissue/cell type enrichment analysis using East Asian-frequent and European-frequent variants according to the risk allele frequencies and identified significant enrichment of adrenal glands in the East Asian-frequent group while the enrichment of arteries and fat tissues was found in the European-frequent group. These findings indicate biological differences in CAD susceptibility between Japanese and Europeans.

CONCLUSIONS

We identified 3 new loci for CAD and highlighted the genetic differences between the Japanese and European populations. Moreover, our transethnic analyses showed both shared and unique genetic architectures between the Japanese and Europeans. While most of the underlying genetic bases for CAD are shared, further analyses in diverse populations will be needed to elucidate variations fully.

Expression Quantitative Trait Loci (eQTL) Mapping in Korean Patients With Crohn's Disease and Identification of Potential Causal Genes Through Integration With Disease Associations

Background

Expression quantitative trait loci (eQTL) datasets have extensively been used to help interpret genome-wide association study signals. Most eQTL analyses have been conducted with populations of European ancestry.

Objective

To determine the most functionally relevant genes at the Crohn’s disease (CD) loci identified in genome-wide association studies (GWAS) involving Asian populations and to find novel disease-associated genes, we conducted an eQTL analysis.

Methods

eQTL analysis was performed using whole-blood RNA-sequencing of 101 Korean patients with CD. FastQTL was used for a pair-wise genome analysis of ∼ 6.5 M SNPs and ∼ 22 K transcripts.

Results

We identified 135,164 cis-eQTL and 3,816 eGenes with a false discovery rate less than 0.05. A significant proportion of the genes identified in our study overlapped with those identified in previous studies. The significantly enriched pathways of these 3,816 eGenes included neutrophil degranulation and small molecule biosynthetic process. Integrated analysis of CD GWAS with Korean eQTL revealed two putative target genes, TNFSF15 and GPR35, at two previously reported loci, whereas TNFSF15 only with the whole blood data from the Genotype-Tissue Expression (GTEx) project, highlighting the utility of building a population-specific data set, even of modest size. The risk alleles of these genes were found to be associated with lower expression levels of TNFSF15 and GPR35, respectively. Our eQTL browser can be accessed at “http://asan.crohneqtl.com/”.

Conclusion

This resource would be useful for studies that need to employ genome-wide association analyses involving Asian populations.

Polymorphisms of BLK are associated with renal disorder in patients with systemic lupus erythematosus

Previous studies are inconclusive on the relationships between BLK gene polymorphisms and clinical features of systemic lupus erythematosus (SLE). The present study aimed to estimate association between BLK loci and SLE clinical features in Chinese population. Associations between BLK single-nucleotide polymorphisms (SNPs) and susceptibility to SLE in this study were estimated using data of 1205 health controls previously reported in the same population. And a total of 814 SLE patients recruited from two different sources according with ACR criteria were analyzed for genotype-phenotype associations. A meta-analysis was conducted of the associations between BLK loci and renal disorder in SLE. The expression quantitative trait locus (eQTL) data were also extracted from the public databases for the selected SNPs. Significant associations were observed between these SNPs and susceptibility to SLE. In addition, the data showed that rs2618479 and rs7812879 were associated with renal disorder [OR = 1.51 (95% CI: 1.15, 1.99) and 1.61 (95% CI: 1.21, 2.14), P_corr = 0.033 and 0.011, respectively] and proteinuria [OR = 1.47 (95% CI: 1.12, 1.95) and 1.52 (95% CI: 1.14, 2.03), P_corr = 0.048 and 0.040, respectively]. The consistent associations were observed in two independent centers as well as new cases group. The result of meta-analysis for rs2618479 was also significant [OR = 1.35 (95% CI: 1.12, 1.62)]. In addition, bioinformatics analysis demonstrated that the two SNPs were significantly associated with the expression of BLK in whole blood and several immune cells. Our data support that variant loci of BLK are associated with presence of renal disorder in patients with SLE.

The single-cell eQTLGen consortium

In recent years, functional genomics approaches combining genetic information with bulk RNA-sequencing data have identified the downstream expression effects of disease-associated genetic risk factors through so-called expression quantitative trait locus (eQTL) analysis. Single-cell RNA-sequencing creates enormous opportunities for mapping eQTLs across different cell types and in dynamic processes, many of which are obscured when using bulk methods. Rapid increase in throughput and reduction in cost per cell now allow this technology to be applied to large-scale population genetics studies. To fully leverage these emerging data resources, we have founded the single-cell eQTLGen consortium (sc-eQTLGen), aimed at pinpointing the cellular contexts in which disease-causing genetic variants affect gene expression. Here, we outline the goals, approach and potential utility of the sc-eQTLGen consortium. We also provide a set of study design considerations for future single-cell eQTL studies.

Allele-specific expression changes dynamically during T cell activation in HLA and other autoimmune loci

Genetic studies have revealed that autoimmune susceptibility variants are over-represented in memory CD4+ T cell regulatory elements1-3. Understanding how genetic variation affects gene expression in different T cell physiological states is essential for deciphering genetic mechanisms of autoimmunity4,5. Here, we characterized the dynamics of genetic regulatory effects at eight time points during memory CD4+ T cell activation with high-depth RNA-seq in healthy individuals. We discovered widespread, dynamic allele-specific expression across the genome, where the balance of alleles changes over time. These genes were enriched fourfold within autoimmune loci. We found pervasive dynamic regulatory effects within six HLA genes. HLA-DQB1 alleles had one of three distinct transcriptional regulatory programs. Using CRISPR-Cas9 genomic editing we demonstrated that a promoter variant is causal for T cell-specific control of HLA-DQB1 expression. Our study shows that genetic variation in cis-regulatory elements affects gene expression in a manner dependent on lymphocyte activation status, contributing to the interindividual complexity of immune responses.

Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels

Identifying the factors that shape protein expression variability in complex multi-cellular organisms has primarily focused on promoter architecture and regulation of single-cell expression in cis. However, this targeted approach has to date been unable to identify major regulators of cell-to-cell gene expression variability in humans. To address this, we have combined single-cell protein expression measurements in the human immune system using flow cytometry with a quantitative genetics analysis. For the majority of proteins whose variability in expression has a heritable component, we find that genetic variants act in trans, with notably fewer variants acting in cis. Furthermore, we highlight using Mendelian Randomization that these variability-Quantitative Trait Loci might be driven by the cis regulation of upstream genes. This indicates that natural selection may balance the impact of gene regulation in cis with downstream impacts on expression variability in trans.

Lymphocyte DNA methylation mediates genetic risk at shared immune-mediated disease loci

Background

Defining regulatory mechanisms through which noncoding risk variants influence the cell-mediated pathogenesis of immune-mediated disease (IMD) has emerged as a priority in the post–genome-wide association study era.

Objectives

With a focus on rheumatoid arthritis, we sought new insight into genetic mechanisms of adaptive immune dysregulation to help prioritize molecular pathways for targeting in this and related immune pathologies.

Methods

Whole-genome methylation and transcriptional data from isolated CD4⁺ T cells and B cells of more than 100 genotyped and phenotyped patients with inflammatory arthritis, all of whom were naive to immunomodulatory treatments, were obtained. Analysis integrated these comprehensive data with genome-wide association study findings across IMDs and other publicly available resources.

Results

We provide strong evidence that disease-associated DNA variants regulate cis-CpG methylation in CD4⁺ T and/or B cells at 37% RA loci. Using paired, cell-specific transcriptomic data and causal inference testing, we identify examples where site-specific DNA methylation in turn mediates gene expression, including FCRL3 in both cell types and ORMDL3/GSDMB, IL6ST/ANKRD55, and JAZF1 in CD4⁺ T cells. A number of genes regulated in this way highlight mechanisms common to RA and other IMDs including multiple sclerosis and asthma, in turn distinguishing them from osteoarthritis, a primarily degenerative disease. Finally, we corroborate the observed effects experimentally.

Conclusions

Our observations highlight important mechanisms of genetic risk in RA and the wider context of immune dysregulation. They confirm the utility of DNA methylation profiling as a tool for causal gene prioritization and, potentially, therapeutic targeting in complex IMD.

GWAS of five gynecologic diseases and cross-trait analysis in Japanese

We performed genome-wide association studies of five gynecologic diseases using data of 46,837 subjects (5236 uterine fibroid, 645 endometriosis, 647 ovarian cancer (OC), 909 uterine endometrial cancer (UEC), and 538 uterine cervical cancer (UCC) cases allowing overlaps, and 39,556 shared female controls) from Biobank Japan Project. We used the population-specific imputation reference panel (n = 3541), yielding 7,645,193 imputed variants. Analyses performed under logistic model, linear mixed model, and model incorporating correlations identified nine significant associations with three gynecologic diseases including four novel findings (rs79219469:C > T, LINC02183, P = 3.3 × 10⁻⁸ and rs567534295:C > T, BRCA1, P = 3.1 × 10⁻⁸ with OC, rs150806792:C > T, INS-IGF2, P = 4.9 × 10⁻⁸ and rs140991990:A > G, SOX9, P = 3.3 × 10⁻⁸ with UCC). Random-effect meta-analysis of the five GWASs correcting for the overlapping subjects suggested one novel shared risk locus (rs937380553:A > G, LOC730100, P = 2.0 × 10⁻⁸). Reverse regression analysis identified three additional novel associations (rs73494486:C > T, GABBR2, P = 4.8 × 10⁻⁸, rs145152209:A > G, SH3GL3/BNC1, P = 3.3 × 10⁻⁸, and rs147427629:G > A, LOC107985484, P = 3.8 × 10⁻⁸). Estimated heritability ranged from 0.026 for OC to 0.220 for endometriosis. Genetic correlations were relatively strong between OC and UEC, endometriosis and OC, and uterine fibroid and OC (r_g > 0.79) compared with relatively weak correlations between UCC and the other four (r_g = −0.08 ~ 0.25). We successfully identified genetic associations with gynecologic diseases in the Japanese population. Shared genetic effects among multiple related diseases may help understanding the pathophysiology.

Integrative analysis of genome-wide association study and expression quantitative trait loci datasets identified various immune cell-related pathways for rheumatoid arthritis

Rheumatoid arthritis (RA) is an autoimmune chronic disorder manifesting as warm, swollen, and painful joints. Multiple immune cells are implicated in the development of RA. Previous studies demonstrated that integrating the genetic information of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTLs) is capable of identifying new disease-risk loci and providing novel insights into the etiology of complex human disease. In this study, we conducted an integrative pathway association analysis of RA by using GWAS summary data and five immune cell types related to eQTL datasets of RA. After combining the cell-specific eQTLs and GWAS summary of RA and performing a pathway-enrichment analysis, we detected a group of RA-associated pathways with common or cell-specific enriched in the five immune cell types. 41 pathways for B cells, 33 pathways for CD4⁺ T cells, 27 pathways for CD8⁺ T cells, 39 pathways for monocyte, and 25 pathways for natural killer cells are significant in RA, among which 48% are common pathways and 32% are cell-specific pathways. We detected a group of RA-associated eQTL pathways related to five different immune cell types. Our findings may provide novel insights into the pathogenesis of RA.

The DNA Repair Nuclease MRE11A Functions as a Mitochondrial Protector and Prevents T Cell Pyroptosis and Tissue Inflammation

In the autoimmune disease rheumatoid arthritis (RA), CD4+ T cells promote pro-inflammatory effector functions by shunting glucose away from glycolysis and ATP production. Underlying mechanisms remain unknown, and here we implicate the DNA repair nuclease MRE11A in the cells' bioenergetic failure. MRE11A deficiency in RA T cells disrupted mitochondrial oxygen consumption and suppressed ATP generation. Also, MRE11A loss of function caused leakage of mitochondrial DNA (mtDNA) into the cytosol, triggering inflammasome assembly, caspase-1 activation, and pyroptotic cell death. Caspase-1 activation was frequent in lymph-node-residing T cells in RA patients. In vivo, pharmacologic and genetic inhibition of MRE11A resulted in tissue deposition of mtDNA, caspase-1 proteolysis, and aggressive tissue inflammation. Conversely, MRE11A overexpression restored mitochondrial fitness and shielded tissue from inflammatory attack. Thus, the nuclease MRE11A regulates a mitochondrial protection program, and MRE11A deficiency leads to DNA repair defects, energy production, and failure and loss of tissue homeostasis.

Identification of Novel T1D Risk Loci and Their Association With Age and Islet Function at Diagnosis in Autoantibody-Positive T1D Individuals: Based on a Two-Stage Genome-Wide Association Study

OBJECTIVE

Type 1 diabetes (T1D) is a highly heritable disease with much lower incidence but more adult-onset cases in the Chinese population. Although genome-wide association studies (GWAS) have identified >60 T1D loci in Caucasians, less is known in Asians.

RESEARCH DESIGN AND METHODS

We performed the first two-stage GWAS of T1D using 2,596 autoantibody-positive T1D case subjects and 5,082 control subjects in a Chinese Han population and evaluated the associations between the identified T1D risk loci and age and fasting C-peptide levels at T1D diagnosis.

RESULTS

We observed a high genetic correlation between children/adolescents and adult T1D case subjects (r _g = 0.87), as well as subgroups of autoantibody status (r _g ≥ 0.90). We identified four T1D risk loci reaching genome-wide significance in the Chinese Han population, including two novel loci, rs4320356 near BTN3A1 (odds ratio [OR] 1.26, P = 2.70 × 10^-8) and rs3802604 in GATA3 (OR 1.24, P = 2.06 × 10^-8), and two previously reported loci, rs1770 in MHC (OR 4.28, P = 2.25 × 10^-232) and rs705699 in SUOX (OR 1.46, P = 7.48 × 10^-20). Further fine mapping in the MHC region revealed five independent variants, including another novel locus, HLA-C position 275 (omnibus P = 9.78 × 10^-12), specific to the Chinese population. Based on the identified eight variants, we achieved an area under the curve value of 0.86 (95% CI 0.85-0.88). By building a genetic risk score (GRS) with these variants, we observed that the higher GRS were associated with an earlier age of T1D diagnosis (P = 9.08 × 10^-11) and lower fasting C-peptide levels (P = 7.19 × 10^-3) in individuals newly diagnosed with T1D.

CONCLUSIONS

Our results extend current knowledge on genetic contributions to T1D risk. Further investigations in different populations are needed for genetic heterogeneity and subsequent precision medicine.

Biological characterization of expression quantitative trait loci (eQTLs) showing tissue-specific opposite directional effects

Interpreting the susceptible loci documented by genome-wide association studies (GWASs) is of utmost importance in the post-GWAS era. Since most complex traits are contributed by multiple tissues, analyzing tissue-specific effects of expression quantitative trait loci (eQTLs) is a promising approach. Here we describe “opposite eQTL effects”, i.e., gene expression effects of eQTLs that are in the opposite direction between different tissues, as the biologically meaningful annotations of genes and genetic variants for understanding the GWAS loci. The genes and single-nucleotide polymorphisms (SNPs) associated with the opposite eQTL effects (opp-multi-eQTL-Genes and opp-multi-eQTL-SNPs) were extracted from the largest eQTL database provided by the Genotype-Tissue Expression (GTEx) project (release version 7). The opposite eQTL effects were detected even between closely related tissues such as cerebellum and brain cortex, and a significant proportion of the genes having eQTLs were annotated as the opp-multi-eQTL-Genes (2,323 out of 31,212; 7.4%). The opp-multi-eQTL-SNPs showed locational enrichment at the transcription start site and also possible involvement of epigenetic regulation. The biological importance of the opposite eQTL effects was also assessed using the SNPs reported in GWASs (GWAS-SNPs), which demonstrated that a high proportion of the opp-multi-eQTL-SNPs are in linkage disequilibrium with the GWAS-SNPs (2,498 out of 9,290; 26.9%). Based on the results, the opposite eQTL effects can be a common phenomenon in the tissue-specific gene regulation with a possible contribution to the development of complex traits.

A Combined Transcriptomic and Genomic Analysis Identifies a Gene Signature Associated With the Response to Anti-TNF Therapy in Rheumatoid Arthritis

Background: Rheumatoid arthritis (RA) is the most frequent autoimmune disease involving the joints. Although anti-TNF therapies have proven effective in the management of RA, approximately one third of patients do not show a significant clinical response. The objective of this study was to identify new genetic variation associated with the clinical response to anti-TNF therapy in RA.

Methods: We performed a sequential multi-omic analysis integrating different sources of molecular information. First, we extracted the RNA from synovial biopsies of 11 RA patients starting anti-TNF therapy to identify gene coexpression modules (GCMs) in the RA synovium. Second, we analyzed the transcriptomic association between each GCM and the clinical response to anti-TNF therapy. The clinical response was determined at week 14 using the EULAR criteria. Third, we analyzed the association between the GCMs and anti-TNF response at the genetic level. For this objective, we used genome-wide data from a cohort of 348 anti-TNF treated patients from Spain. The GCMs that were significantly associated with the anti-TNF response were then tested for validation in an independent cohort of 2,706 anti-TNF treated patients. Finally, the functional implication of the validated GCMs was evaluated via pathway and cell type epigenetic enrichment analyses.

Results: A total of 149 GCMs were identified in the RA synovium. From these, 13 GCMs were found to be significantly associated with anti-TNF response (P < 0.05). At the genetic level, we detected two of the 13 GCMs to be significantly associated with the response to adalimumab (P = 0.0015) and infliximab (P = 0.021) in the Spain cohort. Using the independent cohort of RA patients, we replicated the association of the GCM associated with the response to adalimumab (P = 0.0019). The validated module was found to be significantly enriched for genes involved in the nucleotide metabolism (P = 2.41e-5) and epigenetic marks from immune cells, including CD4+ regulatory T cells (P = 0.041).

Conclusions: These findings show the existence of a drug-specific genetic basis for anti-TNF response, thereby supporting treatment stratification in the search for response biomarkers in RA.

Identification of rare coding variants in TYK2 protective for rheumatoid arthritis in the Japanese population and their effects on cytokine signalling

OBJECTIVE

Although genome-wide association studies (GWAS) have identified approximately 100 loci for rheumatoid arthritis (RA), the disease mechanisms are not completely understood. We evaluated the pathogenesis of RA by focusing on rare coding variants.

METHODS

The coding regions of 98 candidate genes identified by GWAS were sequenced in 2294 patients with RA and 4461 controls in Japan. An association analysis was performed using cases and controls for variants, genes and domains of TYK2. Cytokine responses for two associated variants (R231W, rs201917359; and R703W, rs55882956) in TYK2 as well as a previously reported risk variant (P1004A, rs34536443) for multiple autoimmune diseases were evaluated by reporter assays.

RESULTS

A variant in TYK2 (R703W) showed a suggestive association (p=5.47×10^-8, OR=0.48). We observed more accumulation of rare coding variants in controls in TYK2 (p=3.94×10^-12, OR=0.56). The four-point-one, ezrin, radixin, moesin (FERM; 2.14×10^-3, OR=0.66) and pseudokinase domains (1.63×10^-8, OR=0.52) of TYK2 also showed enrichment of variants in controls. R231W in FERM domain especially reduced interleukin (IL)-6 and interferon (IFN)-γ signalling, whereas P1104A in kinase domain reduced IL-12, IL-23 and IFN-α signalling. R703W in pseudokinase domain reduced cytokine signals similarly to P1104A, but the effects were weaker than those of P1104A.

CONCLUSIONS

The FERM and pseudokinase domains in TYK2 were associated with the risk of RA in the Japanese population. Variants in TYK2 had different effects on cytokine signalling, suggesting that the regulation of selective cytokine signalling is a target for RA treatment.

IMPACT: Genomic Annotation of Cell-State-Specific Regulatory Elements Inferred from the Epigenome of Bound Transcription Factors

Despite significant progress in annotating the genome with experimental methods, much of the regulatory noncoding genome remains poorly defined. Here we assert that regulatory elements may be characterized by leveraging local epigenomic signatures where specific transcription factors (TFs) are bound. To link these two features, we introduce IMPACT, a genome annotation strategy that identifies regulatory elements defined by cell-state-specific TF binding profiles, learned from 515 chromatin and sequence annotations. We validate IMPACT using multiple compelling applications. First, IMPACT distinguishes between bound and unbound TF motif sites with high accuracy (average AUPRC 0.81, SE 0.07; across 8 tested TFs) and outperforms state-of-the-art TF binding prediction methods, MocapG, MocapS, and Virtual ChIP-seq. Second, in eight tested cell types, RNA polymerase II IMPACT annotations capture more cis-eQTL variation than sequence-based annotations, such as promoters and TSS windows (25% average increase in enrichment). Third, integration with rheumatoid arthritis (RA) summary statistics from European (N = 38,242) and East Asian (N = 22,515) populations revealed that the top 5% of CD4+ Treg IMPACT regulatory elements capture 85.7% of RA h2, the most comprehensive explanation for RA h2 to date. In comparison, the average RA h2 captured by compared CD4+ T histone marks is 42.3% and by CD4+ T specifically expressed gene sets is 36.4%. Lastly, we find that IMPACT may be used in many different cell types to identify complex trait associated regulatory elements.

CCL5 and related genes might be the potential diagnostic biomarkers for the therapeutic strategies of rheumatoid arthritis

OBJECTIVE

Rheumatoid arthritis (RA) is a common disease of rheumatic diseases. The aim of this study was to identify gene signatures in RA and uncover their potential mechanisms.

METHOD

Gene expression profiles of GSE1919, GSE55235, GSE55457, and GSE77928 were downloaded from GEO database. The above four series contained 76 samples, including 44 RA patients and 32 normal controls. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and protein-protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed by Cytoscape software.

RESULTS

Up-regulated DEGs were significantly enriched in biological processes, including immune response, positive regulation of immune system process and regulation of immune system process, while down-regulated DEGs were significantly enriched in biological processes, including response to oxygen-containing compound, cellular lipid metabolic process, and lipid metabolic process. KEGG pathway analysis showed the up-regulated DEGs were enriched in cytokine-cytokine receptor interaction, chemokine signaling pathway, and primary immunodeficiency. The 104 hub genes, which were significantly differently expressed between patients and normal controls in at least two datasets, were identified from the PPI network, and subnetworks revealed that these genes were involved in significant pathways, including cytokine-cytokine receptor interaction, chemokine signaling pathway, and primary immunodeficiency.

CONCLUSION

The present study indicated that the identified DEGs and hub genes promote our understanding of molecular mechanisms underlying the development of RA, such as C-C motif chemokine 5 (CCL5), might have a negative impact in the development of RA. CCL5 and its related genes might be the potential diagnostic biomarkers for the therapeutic strategies of RA.

Genetic variants differentially associated with rheumatoid arthritis and systemic lupus erythematosus reveal the disease-specific biology

Two rheumatic autoimmune diseases, rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), have distinct clinical features despite their genetic similarities. We hypothesized that disease-specific variants exclusively associated with only one disease could contribute to disease-specific phenotypes. We calculated the strength of disease specificity for each variant in each disease against the other disease using summary association statistics reported in the largest genome-wide association studies of RA and SLE. Most of highly disease-specific associations were explained by non-coding variants that were significantly enriched within regulatory regions (enhancers or H3K4me3 histone modification marks) in specific cell or organ types. (e.g., In RA, regulatory T primary cells, CD4+ memory T primary cells, thymus and lung; In SLE, CD19+ B primary cells, mobilized CD34+ primary cells, regulatory T primary cells and monocytes). Consistently, genes in the disease-specific loci were significantly involved in T cell- and B cell-related gene sets in RA and SLE. In summary, this study identified disease-specific variants between RA and SLE, and provided statistical evidence for disease-specific cell types, organ and gene sets that may drive the disease-specific phenotypes.

PLD4 is a genetic determinant to systemic lupus erythematosus and involved in murine autoimmune phenotypes

Objectives

Systemic lupus erythematosus (SLE) is an autoimmune disease that is characterised by autoantibody production and widespread inflammation damaging many organs. Previous genome-wide association studies (GWASs) have revealed over 80 genetic determinants of SLE, but they collectively explain a fraction of the heritability, and only a few were proven in vivo for the involvement in SLE. We conducted a meta-analysis of SLE GWAS in the Japanese population, followed by functional analyses of a susceptibility gene with use of mutant mice.

Methods

We conducted a meta-analysis of two GWASs comprising a total of 1363 cases and 5536 controls using the 1000 Genome Project data as an imputation reference. Enrichment analyses for functional annotations were conducted. We examined Phospholipase D4 (Pld4) mutant mice to assess functional involvement of a genetic determinant.

Results

We found a total of 14 significant loci, which included rs2582511 in AHNAK2/PLD4 recently reported in a Chinese study and a novel locus of rs143181706 in MAMLD1 (p=7.9×10−11 and 3.7×10–8, respectively). PLD4 risk allele was associated with anti-dsDNA antibody production. Enrichment analysis of genetic signals revealed involvement of a wide range of immune-related cells and pathways. Pld4 mutant mice revealed remarkably low body weight. The mice demonstrated autoimmune phenotypes compatible with SLE, including splenomegaly and lymphadenopathy, expansion of B cells and hypersecretion of BAFF and production of autoantibodies especially anti-nuclear antibody and anti-dsDNA antibody.

Conclusions

 We found a novel susceptibility gene to SLE. Pld4 mutant mice revealed autoimmune phenotypes suggesting functional involvement of PLD4 with the basics of SLE.

Genetics of rheumatoid arthritis: 2018 status

Study of the genetics of rheumatoid arthritis (RA) began about four decades ago with the discovery of HLA-DRB1 Since the beginning of this century, a number of non-HLA risk loci have been identified through genome-wide association studies (GWAS). We now know that over 100 loci are associated with RA risk. Because genetic information implies a clear causal relationship to the disease, research into the pathogenesis of RA should be promoted. However, only 20% of GWAS loci contain coding variants, with the remaining variants occurring in non-coding regions, and therefore, the majority of causal genes and causal variants remain to be identified. The use of epigenetic studies, high-resolution mapping of open chromatin, chromosomal conformation technologies and other approaches could identify many of the missing links between genetic risk variants and causal genetic components, thus expanding our understanding of RA genetics.

ChIP-Atlas: a data-mining suite powered by full integration of public ChIP-seq data

We have fully integrated public chromatin chromatin immunoprecipitation sequencing (ChIP-seq) and DNase-seq data (n > 70,000) derived from six representative model organisms (human, mouse, rat, fruit fly, nematode, and budding yeast), and have devised a data-mining platform-designated ChIP-Atlas (http://chip-atlas.org). ChIP-Atlas is able to show alignment and peak-call results for all public ChIP-seq and DNase-seq data archived in the NCBI Sequence Read Archive (SRA), which encompasses data derived from GEO, ArrayExpress, DDBJ, ENCODE, Roadmap Epigenomics, and the scientific literature. All peak-call data are integrated to visualize multiple histone modifications and binding sites of transcriptional regulators (TRs) at given genomic loci. The integrated data can be further analyzed to show TR-gene and TR-TR interactions, as well as to examine enrichment of protein binding for given multiple genomic coordinates or gene names. ChIP-Atlas is superior to other platforms in terms of data number and functionality for data mining across thousands of ChIP-seq experiments, and it provides insight into gene regulatory networks and epigenetic mechanisms.

Transcriptome analysis of peripheral blood from patients with rheumatoid arthritis: a systematic review

In the era of precision medicine, transcriptome analysis of whole gene expression is an essential technology. While DNA microarray has a limited dynamic range and a problem of background hybridization, RNA sequencing (RNA-seq) has a broader dynamic range and a lower background signal that increase the sensitivity and reproducibility. While transcriptome analyses in rheumatoid arthritis (RA) have generally focused on whole peripheral blood mononuclear cells (PBMC), analyses of detailed cell subsets have an increased need for understanding the pathophysiology of disease because the involvement of CD4⁺ T cells in the pathogenesis of RA has been established. Transcriptome analysis of detailed CD4⁺ T cell subsets or neutrophils shed new light on the pathophysiology of RA. There are several analyses about the effect of biological treatment. Many studies report the association between type I interferon signature gene expression and response to therapy.

Renal compartment-specific genetic variation analyses identify new pathways in chronic kidney disease

Chronic kidney disease (CKD), a condition in which the kidneys are unable to clear waste products, affects 700 million people globally. Genome-wide association studies (GWASs) have identified sequence variants for CKD; however, the biological basis of these GWAS results remains poorly understood. To address this issue, we created an expression quantitative trait loci (eQTL) atlas for the glomerular and tubular compartments of the human kidney. Through integrating the CKD GWAS with eQTL, single-cell RNA sequencing and regulatory region maps, we identified novel genes for CKD. Putative causal genes were enriched for proximal tubule expression and endolysosomal function, where DAB2, an adaptor protein in the TGF-β pathway, formed a central node. Functional experiments confirmed that reducing Dab2 expression in renal tubules protected mice from CKD. In conclusion, compartment-specific eQTL analysis is an important avenue for the identification of novel genes and cellular pathways involved in CKD development and thus potential new opportunities for its treatment.

Immune-bone interplay in the structural damage in rheumatoid arthritis

The immune and bone systems maintain homeostasis by interacting closely with each other. Rheumatoid arthritis is a pathological consequence of their interplay, as activated T cell immune responses result in osteoclast-mediated bone erosion. An imbalance between forkhead box protein 3 (Foxp3)⁺ regulatory T (T_reg ) cells and T helper type 17 (Th17) cells is often linked with autoimmune diseases, including arthritis. Th17 cells contribute to the bone destruction in arthritis by up-regulating receptor activator of nuclear factor kappa-Β ligand (RANKL) on synovial fibroblasts as well as inducing local inflammation. Studies on the origin of Th17 cells in inflammation have shed light on the pathogenic conversion of Foxp3⁺ T cells. Th17 cells converted from Foxp3⁺ T cells (exFoxp3 Th17 cells) comprise the most potent osteoclastogenic T cell subset in inflammatory bone loss. It has been suggested that osteoclastogenic T cells may have developed originally to stop local infection in periodontitis by inducing tooth loss. In addition, Th17 cells also contribute to the pathogenesis of arthritis by modulating antibody function. Antibodies and immune complexes have attracted considerable attention for their direct role in osteoclastogenesis, and a specific T cell subset in joints was shown to be involved in B cell antibody production. Here we summarize the recent advances in our understanding of the immune-bone interplay in the context of the bone destruction in arthritis.

GWAS-identified CCR1 and IL10 loci contribute to M1 macrophage-predominant inflammation in Behçet's disease

BACKGROUND

Low C-C chemokine receptor 1 (CCR1) and interleukin (IL)-10 expression is associated with risk of Behçet's disease (BD). The objective of the present study was to clarify the pathological roles of CCR1 and IL10 loci identified by previous BD genome-wide association studies (GWASs).

METHODS

M1 and M2 macrophages (Mφ) were differentiated with granulocyte-macrophage colony-stimulating factor or macrophage colony-stimulating factor (M-CSF) from peripheral monocytes of healthy control subjects (HC) and patients with BD. Expression of CD68 and CD163 was evaluated to test for Mφ polarization. CCR1 and IL-10 messenger RNA (mRNA) and protein expression was compared according to CCR1 and IL10 single-nucleotide polymorphism (SNP) genotypes. The migratory ability of M1 and M2 Mφ toward CCR1 ligand macrophage inflammatory protein (MIP)-1α was compared. The ratio of M1 and M2 Mφ in skin lesions of BD and systemic sclerosis (SSc), which was reported to be M2 Mφ-dominant, was compared. To examine the plasticity of polarized Mφ, the differentiated cells were cultured with either the same or the other culture condition.

RESULTS

Preferential expression of CD163, CCR1, and IL-10 was found in M2 Mφ compared with M1 Mφ. M2 Mφ migrated more sensitively to low concentrations of MIP-1α than M1 Mφ did. BD-derived M1 Mφ showed higher CCR1 surface expression than HC-derived M1 Mφ did. IL10 and CCR1 mRNA expression differences were observed by GWAS-identified SNP genotypes in polarized Mφ. BD skin lesions showed M1 Mφ predominance compared with SSc skin lesions. A plasticity assay revealed that M-CSF restored IL-10 synthesis and reduced IL-6 production by M1 Mφ.

CONCLUSIONS

The present study reveals that GWAS-identified SNPs contribute to M1 Mφ-predominant inflammation in BD. Our data also suggest that the skewed Mφ polarization is correctable by immunological intervention.

Deep whole-genome sequencing reveals recent selection signatures linked to evolution and disease risk of Japanese

Understanding natural selection is crucial to unveiling evolution of modern humans. Here, we report natural selection signatures in the Japanese population using 2234 high-depth whole-genome sequence (WGS) data (25.9×). Using rare singletons, we identify signals of very recent selection for the past 2000–3000 years in multiple loci (ADH cluster, MHC region, BRAP-ALDH2, SERHL2). In large-scale genome-wide association study (GWAS) dataset (n = 171,176), variants with selection signatures show enrichment in heterogeneity of derived allele frequency spectra among the geographic regions of Japan, highlighted by two major regional clusters (Hondo and Ryukyu). While the selection signatures do not show enrichment in archaic hominin-derived genome sequences, they overlap with the SNPs associated with the modern human traits. The strongest overlaps are observed for the alcohol or nutrition metabolism-related traits. Our study illustrates the value of high-depth WGS to understand evolution and their relationship with disease risk.

Recent natural selection left signals in human genomes. Here, Okada et al. generate high-depth whole-genome sequence (WGS) data (25.9×) from 2,234 Japanese people of the BioBank Japan Project (BBJ), and identify signals of recent natural selection which overlap variants associated with human traits.

Rheumatology in East Asia

Europe and North America have been leaders in rheumatology for many years. However, for more than a decade now the East Asian region has been catching up dramatically. Some aspects of rheumatology in East Asia are now almost comparable to those in the European League Against Rheumatism (EULAR) and the American College of Rheumatology (ACR). In this article, we describe recent progress in rheumatology in East Asia, focusing specifically on Japan, Korea, and China.

CD4+ and B Lymphocyte Expression Quantitative Traits at Rheumatoid Arthritis Risk Loci in Patients With Untreated Early Arthritis: Implications for Causal Gene Identification

OBJECTIVE

Rheumatoid arthritis (RA) is a genetically complex disease of immune dysregulation. This study sought to gain further insight into the genetic risk mechanisms of RA by conducting an expression quantitative trait locus (eQTL) analysis of confirmed genetic risk loci in CD4+ T cells and B cells from carefully phenotyped patients with early arthritis who were naive to therapeutic immunomodulation.

METHODS

RNA and DNA were isolated from purified B and/or CD4+ T cells obtained from the peripheral blood of 344 patients with early arthritis. Genotyping and global gene expression measurements were carried out using Illumina BeadChip microarrays. Variants in linkage disequilibrium (LD) with non-HLA RA single-nucleotide polymorphisms (defined as r2 ≥ 0.8) were analyzed, seeking evidence of cis- or trans-eQTLs according to whether the associated probes were or were not within 4 Mb of these LD blocks.

RESULTS

Genes subject to cis-eQTL effects that were common to both CD4+ and B lymphocytes at RA risk loci were FADS1, FADS2, BLK, FCRL3, ORMDL3, PPIL3, and GSDMB. In contrast, those acting on METTL21B, JAZF1, IKZF3, and PADI4 were unique to CD4+ lymphocytes, with the latter candidate risk gene being identified for the first time in this cell subset. B lymphocyte-specific eQTLs for SYNGR1 and CD83 were also found. At the 8p23 BLK-FAM167A locus, adjacent genes were subject to eQTLs whose activity differed markedly between cell types; in particular, the FAM167A effect displayed striking B lymphocyte specificity. No trans-eQTLs approached experiment-wide significance, and linear modeling did not identify a significant influence of biologic covariates on cis-eQTL effect sizes.

CONCLUSION

These findings further refine the understanding of candidate causal genes in RA pathogenesis, thus providing an important platform from which downstream functional studies, directed toward particular cell types, may be prioritized.

Pathophysiological mechanisms of autoimmunity

Autoimmune diseases (AIDs) are chronic disorders characterized by inflammatory reactions against self-antigens that can be either systemic or organ specific. AIDs can differ in their epidemiologic features and clinical presentations, yet all share a remarkable complexity. AIDs result from an interplay of genetic and epigenetic factors with environmental components that are associated with imbalances in the immune system. Many of the pathogenic mechanisms of AIDs are also implicated in myasthenia gravis (MG), an AID in which inflammation of the thymus leads to a neuromuscular disorder. Our goal here is to highlight the similarities and differences between MG and other AIDs by reviewing the common transcriptome signatures and the development of germinal centers and by discussing some unresolved questions about autoimmune mechanisms. This review will propose hypotheses to explain the origin of regulatory T (T_reg ) cell defects and the causes of chronicity and specificity of AIDs.

The Four-Way Stop Sign: Viruses, 12-Lipoxygenase, Islets, and Natural Killer Cells in Type 1 Diabetes Progression

Natural killer (NK) cells represent an important effector arm against viral infection, and mounting evidence suggests that viral infection plays a role in the development of type 1 diabetes (T1D) in at least a portion of patients. NK cells recognize their target cells through a delicate balance of inhibitory and stimulatory receptors on their surface. If unbalanced, NK cells have great potential to wreak havoc in the pancreas due to the beta cell expression of the as-yet-defined NKp46 ligand through interactions with the activating NKp46 receptor found on the surface of most NK cells. Blocking interactions between NKp46 and its ligand protects mice from STZ-induced diabetes, but differential expression non-diabetic and diabetic donor samples have not been tested. Additional studies have shown that peripheral blood NK cells from human T1D patients have altered phenotypes that reduce the lytic and functional ability of the NK cells. Investigations of humanT1D pancreas tissues have indicated that the presence of NK cells may be beneficial despite their infrequent detection. In non-obese diabetic (NOD) mice, we have noted that NK cells express high levels of the proinflammatory mediator 12/15-lipoxygenase (12/15-LO), and decreased levels of stimulatory receptors. Conversely, NK cells of 12/15-LO deficient NOD mice, which are protected from diabetes development, express significantly higher levels of stimulatory receptors. Furthermore, the human NK92 cell line expresses the ALOX12 protein [human 12-lipoxygenase (12-LO), related to mouse 12/15-LO] via Western blotting. Human 12-LO is upregulated in the pancreas of both T1D and T2D human donors with insulin-containing islets, showing a link between 12-LO expression and diabetes progression. Therefore, our hypothesis is that NK cells in those susceptible to developing T1D are unable to function properly during viral infections of pancreatic beta cells due to increased 12-LO expression and activation, which contributes to increased interferon-gamma production and an imbalance in activating and inhibitory NK cell receptors, and may contribute to downstream autoimmune T cell responses. The work presented here outlines evidence from our lab, as well as published literature, supporting our hypothesis, including novel data.

Genetics of human autoimmunity: From genetic information to functional insights

Genome-wide association studies have identified hundreds of risk variants associated with human autoimmune diseases. Recent evidence suggests that a substantial portion of them affect gene expression in specific cell types. To obtain the functional insights of GWAS findings, comprehensive characterization of genetic variants in human genome is a key task. In parallel with GWAS, many researches in functional genomics have been conducted in the past decade, and our understandings of cell type-specific gene regulatory system have been substantially improved. In this review, we will introduce the main research topics in functional genomics, and explain their utility to understand biological mechanisms of autoimmune diseases.