Genetic sharing and heritability of paediatric age of onset autoimmune diseases

Integrative analysis reveals novel insights into juvenile idiopathic arthritis pathogenesis and shared molecular pathways with associated traits

Background

Juvenile idiopathic arthritis (JIA) is an autoimmune joint disease that frequently co-occurs with other complex phenotypes, including cancers and other autoimmune diseases. Despite the identification of numerous risk variants through genome-wide association studies (GWAS), the affected genes, their connection to JIA pathogenesis, and their role in the development of associated traits remain unclear. This study aims to address these gaps by elucidating the gene-regulatory mechanisms underlying JIA pathogenesis and exploring its potential role in the emergence of associated traits.

Methods

A two-sample Mendelian Randomization (MR) analysis was conducted to identify blood-expressed genes causally linked to JIA. A curated protein interaction network was subsequently used to identify sets of single-nucleotide polymorphisms (i.e., spatial eQTL SNPs) that regulate the expression of JIA causal genes and their protein interaction partners. These SNPs were cross-referenced against the GWAS catalog to identify statistically enriched traits associated with JIA.

Results

The two-sample MR analysis identified 52 genes whose expression changes in the blood are putatively causal for JIA. These genes (e.g., HLA, LTA, LTB, IL6ST) participate in a range of immune-related pathways (e.g., antigen presentation, cytokine signalling) and demonstrate cell type-specific regulatory patterns across different immune cell types (e.g., PPP1R11 in CD4+ T cells). The spatial eQTLs that regulate JIA causal genes and their interaction partners were statistically enriched for GWAS SNPs linked with 95 other traits, including both known and novel JIA-associated traits. This integrative analysis identified genes whose dysregulation may explain the links between JIA and associated traits, such as autoimmune/inflammatory diseases (genes at 6p22.1 locus), Hodgkin lymphoma (genes at 6p21.3 [FKBPL, PBX2, AGER]), and chronic lymphocytic leukemia (BAK1).

Conclusion

Our approach provides a significant advance in understanding the genetic architecture of JIA and associated traits. The results suggest that the burden of associated traits may differ among JIA patients, influenced by their combined genetic risk across different clusters of traits. Future experimental validation of the identified connections could pave the way for refined patient stratification, the discovery of new biomarkers, and shared therapeutic targets.

Unraveling the link between atopic dermatitis and autoimmune diseases in children: Insights from a large-scale cohort study with 15-year follow-up and shared gene ontology analysis

BACKGROUND

Atopic dermatitis and autoimmune diseases are highly heritable conditions that may co-occur from an early age.

METHODS

The primary study is a national administrative cohort study involving 499,428 children born in 2002, tracked until 2017. Atopic dermatitis was defined as five or more principal diagnoses of atopic dermatitis and two or more topical steroid prescriptions. We estimated the risks for the occurrence of 41 autoimmune diseases, controlling for risk factors. In addition, we sourced a gene library from the National Library of Medicine to conduct a comprehensive gene ontology. We used Gene Weaver to identify gene set similarity and clustering, and used GeneMania to generate a network for shared genes.

RESULTS

Exposed and unexposed groups included 39,832 and 159,328 children, respectively. During a mean follow-up of 12 years, the exposed group had an increased risk of autoimmune disease (hazard ratio, 1.27 [95 % confidence interval, 1.23-1.32]) compared to the unexposed group. The hazard ratios of autoimmune illnesses consistently increased with two- and five years lag times and alternative atopic dermatitis definitions. Shared genes between atopic dermatitis and autoimmune diseases were associated with comorbidities such as asthma, bronchiolitis, and specific infections. Genetic interactions of these shared genes revealed clustering in Th1, Th2, Th17, and non-classifiable pathways.

CONCLUSIONS

Atopic dermatitis was significantly associated with an increased risk of subsequent autoimmune disease. we identified the genetically associated disease in atopic dermatitis patients comorbid with autoimmune disease and demonstrated a genetic network between atopic dermatitis and autoimmune diseases.

Large-scale integrative analysis of juvenile idiopathic arthritis for new insight into its pathogenesis

BACKGROUND

Juvenile idiopathic arthritis (JIA) is one of the most prevalent rheumatic disorders in children and is classified as an autoimmune disease (AID). While a robust genetic contribution to JIA etiology has been established, the exact pathogenesis remains unclear.

METHODS

To prioritize biologically interpretable susceptibility genes and proteins for JIA, we conducted transcriptome-wide and proteome-wide association studies (TWAS/PWAS). Then, to understand the genetic architecture of JIA, we systematically analyzed single-nucleotide polymorphism (SNP)-based heritability, a signature of natural selection, and polygenicity. Next, we conducted HLA typing using multi-ethnicity RNA sequencing data. Additionally, we examined the T cell receptor (TCR) repertoire at a single-cell level to explore the potential links between immunity and JIA risk.

RESULTS

We have identified 19 TWAS genes and two PWAS proteins associated with JIA risks. Furthermore, we observe that the heritability and cell type enrichment analysis of JIA are enriched in T lymphocytes and HLA regions and that JIA shows higher polygenicity compared to other AIDs. In multi-ancestry HLA typing, B*45:01 is more prevalent in African JIA patients than in European JIA patients, whereas DQA1*01:01, DQA1*03:01, and DRB1*04:01 exhibit a higher frequency in European JIA patients. Using single-cell immune repertoire analysis, we identify clonally expanded T cell subpopulations in JIA patients, including CXCL13+BHLHE40+ TH cells which are significantly associated with JIA risks.

CONCLUSION

Our findings shed new light on the pathogenesis of JIA and provide a strong foundation for future mechanistic studies aimed at uncovering the molecular drivers of JIA.

Identification of the shared genetic architecture underlying seven autoimmune diseases with GWAS summary statistics

Background

The common clinical symptoms and immunopathological mechanisms have been observed among multiple autoimmune diseases (ADs), but the shared genetic etiology remains unclear.

Methods

GWAS summary statistics of seven ADs were downloaded from Open Targets Genetics and Dryad. Linkage disequilibrium score regression (LDSC) was applied to estimate overall genetic correlations, bivariate causal mixture model (MiXeR) was used to qualify the polygenic overlap, and stratified-LDSC partitioned heritability to reveal tissue and cell type specific enrichments. Ultimately, we conducted a novel adaptive association test called MTaSPUsSet for identifying pleiotropic genes.

Results

The high heritability of seven ADs ranged from 0.1228 to 0.5972, and strong genetic correlations among certain phenotypes varied between 0.185 and 0.721. There was substantial polygenic overlap, with the number of shared SNPs approximately 0.03K to 0.21K. The specificity of SNP heritability was enriched in the immune/hematopoietic related tissue and cells. Furthermore, we identified 32 pleiotropic genes associated with seven ADs, 23 genes were considered as novel genes. These genes were involved in several cell regulation pathways and immunologic signatures.

Conclusion

We comprehensively explored the shared genetic architecture across seven ADs. The findings progress the exploration of common molecular mechanisms and biological processes involved, and facilitate understanding of disease etiology.

Loss of function of XBP1 splicing activity of IRE1α favors B cell tolerance breakdown

Anti-nuclear antibodies are the hallmark of autoimmune diseases such as systemic lupus erythematosus (SLE) and scleroderma. However, the molecular mechanisms of B cell tolerance breakdown in these pathological contexts are poorly known. The study of rare familial forms of autoimmune diseases could therefore help to better describe common biological mechanisms leading to B cell tolerance breakdown. By Whole-Exome Sequencing, we identified a new heterozygous mutation (p.R594C) in ERN1 gene, encoding IRE1α (Inositol-Requiring Enzyme 1α), in a multiplex family with several members presenting autoantibody-mediated autoimmunity. Using human cell lines and a knock-in (KI) transgenic mouse model, we showed that this mutation led to a profound defect of IRE1α ribonuclease activity on X-Box Binding Protein 1 (XBP1) splicing. The KI mice developed a broad panel of autoantibodies, however in a subclinical manner. These results suggest that a decrease of spliced form of XBP1 (XBP1s) production could contribute to B cell tolerance breakdown and give new insights into the function of IRE1α which are important to consider for the development of IRE1α targeting strategies.

Assessment of COVID-19 Morbidity and Mortality Among Patients With Autoimmune Diseases at King Abdulaziz University Hospital

Background The coronavirus disease 2019 (COVID-19) pandemic has raised significant concerns about the effects of the virus on patients with autoimmune diseases. Therefore, understanding the COVID-19 outcomes in this population is crucial for effective prevention and management. Objective This study aimed to investigate the association between autoimmune diseases and the severity of COVID-19 in terms of mortality and morbidity. Despite substantial advancements in pandemic-related research concerning COVID-19 and autoimmune diseases, there remain noteworthy gaps in our comprehension of this association, particularly due to limited investigations conducted in Saudi Arabia. Methods This was a retrospective record review of a tertiary center from January 2020 to January 2022. We included 120 patients, among whom 40 were diagnosed with autoimmune diseases, and 80 were age- and sex-matched controls. Afterward, we assessed their demographics, year of admission, intensive care unit (ICU) admission, health status, length of hospitalization, comorbidities, diagnosis of autoimmune diseases, and type of immunosuppressant therapy. Results Most of the included patients (mean age: 45.4 years) were females (65.8%). The ratio of non-autoimmune diseases to autoimmune diseases was 2:1, the mean length of hospitalization was 8.83 ± 8.16 days, and the median was seven days (interquartile range (IQR) = 3 to 11 days). Among them, 17.5% were admitted to the ICU and 10% died. The prevalence of autoimmune diseases was higher in women than in men (77.5%). The most common diseases were systemic lupus erythematosus (40%), rheumatoid arthritis (20%), and ankylosing spondylitis (10%). Regarding COVID-19 outcomes, ICU admissions were higher among patients with autoimmune diseases than those with non-autoimmune diseases (35% vs. 8.8%) (p<0.05). This trend was also observed in mortality, with a higher percentage of deaths among patients with autoimmune diseases (27.5% vs. 1.7%) (p<0.05). In addition, there were no significant differences between genders in terms of ICU admission, health status outcomes, or length of hospitalization among patients with autoimmune diseases (p>0.05). Notably, 25 patients were administered immunosuppressants. Of these, 18 (72%) used steroids only, while seven (28%) used both biological and steroid therapy. However, no significant associations were observed between the type of treatment used and outcomes such as ICU admission, health status at discharge, and length of hospitalization (p>0.05).  Conclusion This study suggests that individuals with autoimmune diseases have more severe COVID-19 outcomes, as shown by ICU admission and mortality rates, than patients with non-autoimmune diseases. Furthermore, we observed that the use of immunosuppressant medications among patients with autoimmune diseases showed no noticeable effect on these outcomes.

Juvenile idiopathic arthritis-associated genetic loci exhibit spatially constrained gene regulatory effects across multiple tissues and immune cell types

Juvenile idiopathic arthritis (JIA) is an autoimmune, inflammatory joint disease with complex genetic etiology. Previous GWAS have found many genetic loci associated with JIA. However, the biological mechanism behind JIA remains unknown mainly because most risk loci are located in non-coding genetic regions. Interestingly, increasing evidence has found that regulatory elements in the non-coding regions can regulate the expression of distant target genes through spatial (physical) interactions. Here, we used information on the 3D genome organization (Hi-C data) to identify target genes that physically interact with SNPs within JIA risk loci. Subsequent analysis of these SNP-gene pairs using data from tissue and immune cell type-specific expression quantitative trait loci (eQTL) databases allowed the identification of risk loci that regulate the expression of their target genes. In total, we identified 59 JIA-risk loci that regulate the expression of 210 target genes across diverse tissues and immune cell types. Functional annotation of spatial eQTLs within JIA risk loci identified significant overlap with gene regulatory elements (i.e., enhancers and transcription factor binding sites). We found target genes involved in immune-related pathways such as antigen processing and presentation (e.g., ERAP2, HLA class I and II), the release of pro-inflammatory cytokines (e.g., LTBR, TYK2), proliferation and differentiation of specific immune cell types (e.g., AURKA in Th17 cells), and genes involved in physiological mechanisms related to pathological joint inflammation (e.g., LRG1 in arteries). Notably, many of the tissues where JIA-risk loci act as spatial eQTLs are not classically considered central to JIA pathology. Overall, our findings highlight the potential tissue and immune cell type-specific regulatory changes contributing to JIA pathogenesis. Future integration of our data with clinical studies can contribute to the development of improved JIA therapy.

Examining Health Outcomes in Juvenile Idiopathic Arthritis: A Genetic Epidemiology Study

OBJECTIVE

Juvenile idiopathic arthritis (JIA) is the most common pediatric rheumatic disease; however, little is known about its wider health impacts. This study explores health outcomes associated with JIA genetic liability.

METHODS

We used publicly available genetic data sets to interrogate the genetic correlation between JIA and 832 other health-related traits using linkage disequilibrium score regression. Two-sample Mendelian randomization (2SMR) was used to examine four genetic correlates for evidence of causality.

RESULTS

We found robust evidence (adjusted P [P_adj ] < 0.05) of genetic correlation between JIA and rheumatoid arthritis (genetic correlation [r_g ] = 0.63, P_adj  = 0.029), hypothyroidism/myxedema (r_g  = 0.61, P_adj  = 0.041), celiac disease (CD) (r_g  = 0.58, P_adj  = 0.032), systemic lupus erythematosus (r_g  = 0.40, P_adj  = 0.032), coronary artery disease (CAD) (r_g  = 0.42, P_adj  = 0.006), number of noncancer illnesses (r_g  = 0.42, P_adj  = 0.016), paternal health (r_g  = 0.57, P_adj  = 0.032), and strenuous sports (r_g  = -0.52, P_adj  = 0.032). 2SMR analyses found robust evidence that genetic liability to JIA was causally associated with the number of noncancer illnesses reported by UK Biobank (UKBB) participants (increase of 0.03 noncancer illnesses per doubling odds of JIA, 95% confidence interval 0.01-0.05).

CONCLUSION

This study illustrates genetic sharing between JIA and a diversity of health outcomes. The causal association between genetic liability to JIA and noncancer illnesses suggests a need for broader health assessments of patients with JIA to reduce their potential comorbid burden. The strength of genetic correlation with hypothyroidism and CD implies that patients with JIA may benefit from CD and thyroid function screening. Strong positive genetic correlation between JIA and CAD supports the need for cardiovascular risk assessment and risk factor modification.

A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics

Autoimmune diseases share a general mechanism of auto-antigens harming tissues. Still. they are phenotypically diverse, with genetic as well as environmental factors contributing to their etiology at varying degrees. Associated genomic loci and variants have been identified in numerous genome-wide association studies (GWAS), whose results are increasingly used for polygenic scores (PGS) that are used to predict disease risk. At the same time, a technological shift from genotyping arrays to next generation sequencing (NGS) is ongoing. NGS allows the identification of virtually all - including rare - genetic variants, which in combination with methodological developments promises to improve the prediction of disease risk and elucidate molecular mechanisms underlying disease. Here we review current, publicly available autoimmune disease GWAS and PGS data based on information from the GWAS and PGS catalog, respectively. We summarize autoimmune diseases investigated, respective studies conducted and their results. Further, we review genetic data and autoimmune disease patients in the UK Biobank (UKB), the largest resource for genetic and phenotypic data available for academic research. We find that only comparably prevalent autoimmune diseases are covered by the UKB and at the same time assessed by both GWAS and PGS catalogs. These are systemic (systemic lupus erythematosus) as well as organ-specific, affecting the gastrointestinal tract (inflammatory bowel disease as well as specifically Crohn's disease and ulcerative colitis), joints (juvenile ideopathic arthritis, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis), glands (Sjögren syndrome), the nervous system (multiple sclerosis), and the skin (vitiligo).

Multisystem Autoimmune Inflammatory Disease, Including Colitis, Due to Inborn Error of Immunity

Our understanding of inflammatory bowel disease is changing as we identify genetic variants associated with immune dysregulation. Inflammatory bowel disease undetermined, even when diagnosed in older children and adolescents, in the setting of multiple inflammatory and infectious diseases should raise the suspicion of complex immune dysregulation with a monogenic basis. We report a case of inflammatory bowel disease undetermined triggered by exposure to a nonsteroidal antiinflammatory drug in a 16-year-old girl with a background history of juvenile idiopathic arthritis, cytopenias, recurrent respiratory tract and middle ear infections, and esophageal candidiasis. Immunologic assessment included measurement of immunoglobulin levels, lymphocyte immunophenotyping, B-cell functional tests, and whole-exome sequencing. Laboratory investigation revealed defects of humoral immunity, including mild persistent hypogammaglobulinemia affecting all 3 isotypes and absent isohemagglutinins. Whole exome sequencing revealed a heterozygous TNFRSF13B (Tumor Necrosis Factor Receptor Superfamily Member 13B, or Transmembrane Activator and Calcium-modulating cyclophilin ligand Interactor, TACI) gene variant, which is associated with common variable immunodeficiency and the development of autoimmune diseases. In conclusion, a clinical history of recurrent infections, atypical histologic features of inflammatory bowel disease, additional autoimmune manifestations, and an inadequate response to conventional therapy should prompt the physician to refer to an immunologist with the query of inborn error of immunity. We report how extensive immune evaluation and genetic diagnosis can individualize care and facilitate a multidisciplinary team approach.

Prediction of genetic alteration of phospholipase C isozymes in brain disorders: Studies with deep learning

Genetic mutations leading to the development of various diseases, such as cancer, diabetes, and neurodegenerative disorders, can be attributed to multiple mechanisms and exposure to diverse environments. These disorders further increase gene mutation rates and affect the activity of translated proteins, both phenomena associated with cellular responses. Therefore, maintaining the integrity of genetic and epigenetic information is critical for disease suppression and prevention. With the advent of genome sequencing technologies, large-scale genomic data-based machine learning tools, including deep learning, have been used to predict and identify somatic inactivation or negative dominant expression of target genes in various diseases. Although deep learning studies have recently been highlighted for their ability to distinguish between the genetic information of diseases, conventional wisdom is also necessary to explain the correlation between genotype and phenotype. Herein, we summarize the current understanding of phosphoinositide-specific phospholipase C isozymes (PLCs) and an overview of their associations with genetic variation, as well as their emerging roles in several diseases. We also predicted and discussed new findings of cryptic PLC splice variants by deep learning and the clinical implications of the PLC genetic variations predicted using these tools.

Prevalence of autoimmune diseases and other associated conditions in children and young adults with juvenile idiopathic arthritis

Objective

Many autoimmune diseases share common pathogenic mechanisms; however, there are limited studies quantifying the coexistence of autoimmune diseases and associated conditions in patients with juvenile idiopathic arthritis (JIA). This large US-based study estimated and compared the prevalence of multiple coexisting autoimmune diseases in patients with JIA with a general paediatric (GP) patient population.

Methods

This retrospective cohort study was conducted using registry data from the Cincinnati Children’s Hospital Medical Center (January 2010–October 2018). The prevalence of multiple autoimmune diseases was estimated in patients (age <21 years) with JIA and a control group from the GP patient population. Crude prevalences of 26 prespecified autoimmune diseases and associated conditions were compared using Bayesian Poisson regression modelling for each year up to the end of the study period.

Results

Overall, 2026 patients were included in the JIA cohort and 41 572 in the GP cohort. Of 26 autoimmune diseases and associated conditions evaluated, 14 (53.8%) had a significantly higher prevalence in the JIA cohort compared with the GP cohort. In total, seven (26.9%) autoimmune diseases or associated conditions had a >20-fold increased prevalence in the JIA cohort compared with the GP cohort.

Conclusion

In this study, patients with JIA had a greater prevalence of a large number of coexisting autoimmune diseases and associated conditions compared with the GP population. Physicians should consider coexisting autoimmune diseases in the treatment and management of patients with JIA.

Variable immunodeficiency score upfront analytical link (VISUAL), a proposal for combined prognostic score at diagnosis of common variable immunodeficiency

The broad and heterogeneous clinical spectrum that characterizes common variable immunodeficiency (CVID) is associated with quite different disease course and prognosis, highlighting the need to develop tools that predict complications. We developed a multianalyte VISUAL score (variable immunodeficiency score upfront analytical link) aimed to predict severity using individual CVID patient data at baseline of a cohort of 50 CVID patients from two different centers in Portugal and Spain. We retrospectively applied VISUAL to the CVID clinical severity scores proposed by Ameratunga and Grimbacher after 15 years follow-up of our cohort. VISUAL score at CVID diagnosis showed adequate performance for predicting infectious and non-infectious severe complications (Cluster B). Compared to switched memory B lymphocyte phenotype alone, VISUAL provided a more accurate identification of clinically meaningful outcome, with significantly higher sensitivity (85% vs 55%, p = 0.01), and negative predictive value (77% vs 58%) and AUC of the ROC curves (0.72 vs 0.64), with optimal cut-off level of 10. For every increase of 1 point in the VISUAL scale, the odds of being in the higher risk category (Cluster B) increased in 1.3 (p = 0.005) for Ameratunga's severity score and 1.26 (p = 0.004) for Grimbacher's severity score. At diagnosis of CVID, VISUAL score ≥ 10 showed 8.94-fold higher odds of severe prognosis than below this threshold. Kaplan-Meier estimates for the VISUAL ≥ 10 points showed significantly earlier progression to Cluster B than those with VISUAL < 10 (p = 0.0002). This prognostic laboratory score might allow close monitoring and more aggressive treatment in patients with scores ≥ 10 on a personalized basis approach. Further studies are needed to prospectively validate VISUAL score.

Immune-mediated diseases and risk of Crohn's disease or ulcerative colitis: a prospective cohort study

BACKGROUND

Although immune-mediated diseases (IMDs) including inflammatory bowel diseases (IBDs) are known to cluster, to what extent this is due to common environmental influences is unknown.

AIM

To examine the incidence of IBD in individuals with another IMD.

METHODS

We used data from the prospective Nurses' Health Study II cohort (1995-2017) to examine the effect of diagnoses of several common IMDs on subsequent risk of Crohn's disease (CD) or ulcerative colitis (UC) using Cox proportional hazards models, adjusting for detailed diet and lifestyle confounders.

RESULTS

We documented 132 cases of CD and 186 cases of UC over 2 016 163 person-years of follow-up (median age at IBD diagnosis 50 years). Compared to participants with no history of IMD, the HRs of CD for those with 1 and ≥ 2 IMDs were 2.57 (95% CI 1.77-3.74) and 2.74 (95% CI 1.36 to 5.49), respectively (P_trend  < 0.0001). This association was only modestly attenuated by adjustment for environmental risk factors (HR 2.35 and 2.46, respectively). The risk of UC was not increased, with multivariable-adjusted HRs of 1.22 (95% CI 0.85-1.76) and 1.33 (95% CI 0.67-2.65) for those with 1 and ≥ 2 IMDs, respectively, compared to those with none (P_trend 0.16) (P_{heterogeneity} comparing CD and UC 0.037). Asthma, atopic dermatitis, psoriasis and rosacea were individually associated with higher risk of CD (HR ranging from 2.15 to 3.39) but not UC.

CONCLUSIONS

Individuals with one or more IMDs are at an increased risk for CD but not UC.

Association of novel rare coding variants with juvenile idiopathic arthritis

OBJECTIVE

Juvenile idiopathic arthritis (JIA) is the most common type of arthritis among children, but a few studies have investigated the contribution of rare variants to JIA. In this study, we aimed to identify rare coding variants associated with JIA for the genome-wide landscape.

METHODS

We established a rare variant calling and filtering pipeline and performed rare coding variant and gene-based association analyses on three RNA-seq datasets composed of 228 JIA patients in the Gene Expression Omnibus against different sets of controls, and further conducted replication in our whole-exome sequencing (WES) data of 56 JIA patients. Then we conducted differential gene expression analysis and assessed the impact of recurrent functional coding variants on gene expression and signalling pathway.

RESULTS

By the RNA-seq data, we identified variants in two genes reported in literature as JIA causal variants, as well as additional 63 recurrent rare coding variants seen only in JIA patients. Among the 44 recurrent rare variants found in polyarticular patients, 10 were replicated by our WES of patients with the same JIA subtype. Several genes with recurrent functional rare coding variants have also common variants associated with autoimmune diseases. We observed immune pathways enriched for the genes with rare coding variants and differentially expressed genes.

CONCLUSION

This study elucidated a novel landscape of recurrent rare coding variants in JIA patients and uncovered significant associations with JIA at the gene pathway level. The convergence of common variants and rare variants for autoimmune diseases is also highlighted in this study.

Targeted Proteomics Reveals Inflammatory Pathways that Classify Immune Dysregulation in Common Variable Immunodeficiency

Patients with common variable immunodeficiency (CVID) can develop immune dysregulation complications such as autoimmunity, lymphoproliferation, enteritis, and malignancy, which cause significant morbidity and mortality. We aimed to (i) assess the potential of serum proteomics in stratifying patients with immune dysregulation using two independent cohorts and (ii) identify cytokine and chemokine signaling pathways that underlie immune dysregulation in CVID. A panel of 180 markers was measured in two multicenter CVID cohorts using Olink Protein Extension Assay technology. A classification algorithm was trained to distinguish CVID with immune dysregulation (CVIDid, n = 14) from CVID with infections only (CVIDio, n = 16) in the training cohort, and validated on a second testing cohort (CVIDid n = 23, CVIDio n = 24). Differential expression in both cohorts was used to determine relevant signaling pathways. An elastic net classifier using MILR1, LILRB4, IL10, IL12RB1, and CD83 could discriminate between CVIDid and CVIDio patients with a sensitivity of 0.83, specificity of 0.75, and area under the curve of 0.73 in an independent testing cohort. Activated pathways (fold change > 1.5, FDR-adjusted p < 0.05) in CVIDid included Th1 and Th17-associated signaling, as well as IL10 and other immune regulatory markers (LAG3, TNFRSF9, CD83). Targeted serum proteomics provided an accurate and reproducible tool to discriminate between patients with CVIDid and CVIDio. Cytokine profiles provided insight into activation of Th1 and Th17 pathways and indicate a possible role for chronic inflammation and exhaustion in immune dysregulation. These findings serve as a first step towards the development of biomarkers for immune dysregulation in CVID.

Genomic risk scores for juvenile idiopathic arthritis and its subtypes

OBJECTIVES

Juvenile idiopathic arthritis (JIA) is an autoimmune disease and a common cause of chronic disability in children. Diagnosis of JIA is based purely on clinical symptoms, which can be variable, leading to diagnosis and treatment delays. Despite JIA having substantial heritability, the construction of genomic risk scores (GRSs) to aid or expedite diagnosis has not been assessed. Here, we generate GRSs for JIA and its subtypes and evaluate their performance.

METHODS

We examined three case/control cohorts (UK, US-based and Australia) with genome-wide single nucleotide polymorphism (SNP) genotypes. We trained GRSs for JIA and its subtypes using lasso-penalised linear models in cross-validation on the UK cohort, and externally tested it in the other cohorts.

RESULTS

The JIA GRS alone achieved cross-validated area under the receiver operating characteristic curve (AUC)=0.670 in the UK cohort and externally-validated AUCs of 0.657 and 0.671 in the US-based and Australian cohorts, respectively. In logistic regression of case/control status, the corresponding odds ratios (ORs) per standard deviation (SD) of GRS were 1.831 (1.685 to 1.991) and 2.008 (1.731 to 2.345), and were unattenuated by adjustment for sex or the top 10 genetic principal components. Extending our analysis to JIA subtypes revealed that the enthesitis-related JIA had both the longest time-to-referral and the subtype GRS with the strongest predictive capacity overall across data sets: AUCs 0.82 in UK; 0.84 in Australian; and 0.70 in US-based. The particularly common oligoarthritis JIA also had a GRS that outperformed those for JIA overall, with AUCs of 0.72, 0.74 and 0.77, respectively.

CONCLUSIONS

A GRS for JIA has potential to augment clinical JIA diagnosis protocols, prioritising higher-risk individuals for follow-up and treatment. Consistent with JIA heterogeneity, subtype-specific GRSs showed particularly high performance for enthesitis-related and oligoarthritis JIA.

Canalization and Robustness in Human Genetics and Disease

Canalization refers to the evolution of populations such that the number of individuals who deviate from the optimum trait, or experience disease, is minimized. In the presence of rapid cultural, environmental, or genetic change, the reverse process of decanalization may contribute to observed increases in disease prevalence. This review starts by defining relevant concepts, drawing distinctions between the canalization of populations and robustness of individuals. It then considers evidence pertaining to three continuous traits and six domains of disease. In each case, existing genetic evidence for genotype-by-environment interactions is insufficient to support a strong inference of decanalization, but we argue that the advent of genome-wide polygenic risk assessment now makes an empirical evaluation of the role of canalization in preventing disease possible. Finally, the contributions of both rare and common variants to congenital abnormality and adult onset disease are considered in light of a new kerplunk model of genetic effects.

Detecting pathogenic variants in autoimmune diseases using high-throughput sequencing

Sequencing the first human genome in 2003 took 15 years and cost $2.7 billion. Advances in sequencing technologies have since decreased costs to the point where it is now feasible to resequence a whole human genome for $1000 in a single day. These advances have allowed the generation of huge volumes of high‐quality human sequence data used to construct increasingly large catalogs of both population‐level and disease‐causing variation. The existence of such databases, coupled with a high‐quality human reference genome, means we are able to interrogate and annotate all types of genetic variation and identify pathogenic variants for many diseases. Increasingly, sequencing‐based approaches are being used to elucidate the underlying genetic cause of autoimmune diseases, a group of roughly 80 polygenic diseases characterized by abnormal immune responses where healthy tissue is attacked. Although sequence data generation has become routine and affordable, significant challenges remain with no gold‐standard methodology to identify pathogenic variants currently available. This review examines the latest methodologies used to identify pathogenic variants in autoimmune diseases and considers available sequencing options and subsequent bioinformatic methodologies and strategies. The development of reliable and robust sequencing and analytic workflows to detect pathogenic variants is critical to realize the potential of precision medicine programs where patient variant information is used to inform clinical practice.

Co-aggregation and heritability of organ-specific autoimmunity: a population-based twin study

OBJECTIVE

Co-aggregation of autoimmune diseases is common, suggesting partly shared etiologies. Genetic factors are believed to be important, but objective measures of environmental vs heritable influences on co-aggregation are absent. With a novel approach to twin studies, we aimed at estimating heritability and genetic overlap in seven organ-specific autoimmune diseases.

DESIGN

Prospective twin cohort study.

METHODS

We used a cohort of 110 814 twins to examine co-aggregation and heritability of Hashimoto's thyroiditis, atrophic gastritis, celiac disease, Graves' disease, type 1 diabetes, vitiligo and Addison's disease. Hazard ratios (HR) were calculated for twins developing the same or different disease as compared to their co-twin. The differences between monozygotic and dizygotic twin pairs were used to estimate the genetic influence on co-aggregation. Heritability for individual disorders was calculated using structural equational modeling adjusting for censoring and truncation of data.

RESULTS

Co-aggregation was more pronounced in monozygotic twins (median HR: 3.2, range: 2.2-9.2) than in dizygotic twins (median HR: 2.4, range: 1.1-10.0). Heritability was moderate for atrophic gastritis (0.38, 95% CI: 0.23-0.53) but high for all other diseases, ranging from 0.60 (95% CI: 0.49-0.71) for Graves' disease to 0.97 (95% CI: 0.91-1.00) for Addison's disease.

CONCLUSIONS

Overall, co-aggregation was more pronounced in monozygotic than in dizygotic twins, suggesting that disease overlap is largely attributable to genetic factors. Co-aggregation was common, and twins faced up to a ten-fold risk of developing diseases not present in their co-twin. Our results validate and refine previous heritability estimates based on smaller twin cohorts.

Genetic architecture study of rheumatoid arthritis and juvenile idiopathic arthritis

BACKGROUND

Rheumatoid arthritis and juvenile idiopathic arthritis are two types of autoimmune diseases with inflammation at the joints, occurring to adults and children respectively. There are phenotypic overlaps between these two types of diseases, despite the age difference in patient groups.

METHODS

To systematically compare the genetic architecture of them, we conducted analyses at gene and pathway levels and constructed protein-protein-interaction network based on summary statistics of genome-wide association studies of these two diseases. We examined their difference and similarity at each level.

RESULTS

We observed extensive overlap in significant SNPs and genes at the human leukocyte antigen region. In addition, several SNPs in other regions of the human genome were also significantly associated with both diseases. We found significantly associated genes enriched in 32 pathways shared by both diseases. Excluding genes in the human leukocyte antigen region, significant enrichment is present for pathways like interleukin-27 pathway and NO2-dependent interleukin-12 pathway in natural killer cells.

DISCUSSION

The identification of commonly associated genes and pathways may help in finding population at risk for both diseases, as well as shed light on repositioning and designing drugs for both diseases.

Current Understanding and Recent Developments in Common Variable Immunodeficiency Associated Autoimmunity

Common variable immunodeficiency (CVID) is the most prevalent symptomatic primary immunodeficiency and comprises a group of disorders with similar antibody deficiency but a myriad of different etiologies, most of which remain undefined. The variable aspect of CVID refers to the approximately half of patients who develop non-infectious complications in addition to heightened susceptibility to infection. The pathogenesis of these complications is poorly understood and somewhat counterintuitive because these patients that are defined by their immune futility simultaneously have elevated propensity for autoimmune disease. There are numerous aspects of immune dysregulation associated with autoimmunity in CVID that have only begun to be studied. These findings include elevations of T helper type 1 and follicular helper T cells and B cells expressing low levels of CD21 as well as reciprocal decreases in regulatory T cells and isotype-switched memory B cells. Recently, advances in genomics have furthered our understanding of the fundamental biology underlying autoimmunity in CVID and led to precision therapeutic approaches. However, these genetic etiologies are also associated with clinical heterogeneity and incomplete penetrance, highlighting the fact that continued research efforts remain necessary to optimize treatment. Additional factors, such as commensal microbial dysbiosis, remain to be better elucidated. Thus, while recent advances in our understanding of CVID-associated autoimmunity have been exciting and substantial, these current scientific advances must now serve as building blocks for the next stages of discovery.

Micro-RNA 196a2 expression and miR-196a2 (rs11614913) polymorphism in T1DM: a pilot study

Background Recent emerging evidence supports the role of miR-196a2 in various human diseases. However, its role in type 1 diabetes mellitus (T1DM) is still underestimated. We aimed, for the first time, to investigate the expression of miR-196a2 in T1DM and the association of miR-196a2 (rs11614913) polymorphism with susceptibility of T1DM in a sample of patients from Cairo, Egypt. Methods The study included 150 patients and 150 healthy subjects. Evaluation of rs11614913 genotypes and miR-196a2 expression was done using the allelic discrimination and quantitative reverse transcriptase polymerase chain reaction (PCR) method, respectively. Results The Hardy-Weinberg equilibrium of single nucleotide polymorphism(SNP) was detected among controls (p = 0.2). Our results revealed that the TT genotype was more frequent in patients (22.6%) than controls (10%) while the CC genotype was more frequent in controls (47.3%) than patients (39.3%) (p = 0.01). The frequency of the T allele was significantly higher in patients than in controls (41.7 vs. 31.3%), while the C allele was more frequent in controls (p = 0.008). After adjustment for traditional risk factors, the association of the TT genotype with T1DM remained significant (TT vs. CC, odds ration [OR] = 3.2, 95% confidence interval [CI]: 1.4-7.4, p = 0.005). Power analysis of the data yielded a statistical power of 80% for the miR-196a2 rs11614913 with T1DM. Relative expression of miR-196a2 showed significant decrease in patients compared to controls (median = 0.09, 0.5, interquartile range [IQR] = 0.03-1.6, 0.1-2.1). However, miR-196a2 expression showed no significant difference between different rs11614913 genotypes (p = 0.5). Conclusions Our findings demonstrated that miR-196a rs11614913 is associated with T1DM and decreased expression of miR-196a2 may play a role in pathogenesis of T1DM.

Recent advances in elucidating the genetics of common variable immunodeficiency

Common variable immunodeficiency disorders (CVID), a heterogeneous group of inborn errors of immunity, is the most common symptomatic primary immunodeficiency disorder. Patients with CVID have highly variable clinical presentation. With the advent of whole genome sequencing and genome wide association studies (GWAS), there has been a remarkable improvement in understanding the genetics of CVID. This has also helped in understanding the pathogenesis of CVID and has drastically improved the management of these patients. A multi-omics approach integrating the DNA sequencing along with RNA sequencing, proteomics, epigenetic and metabolomics profile is the need of the hour to unravel specific CVID associated disease pathways and novel therapeutic targets. In this review, we elaborate various techniques that have helped in understanding the genetics of CVID.

Moving towards a molecular taxonomy of autoimmune rheumatic diseases

Autoimmune rheumatic diseases pose many problems that have, in general, already been solved in the field of cancer. The heterogeneity of each disease, the clinical similarities and differences between different autoimmune rheumatic diseases and the large number of patients that remain without a diagnosis underline the need to reclassify these diseases via new approaches. Knowledge about the molecular basis of systemic autoimmune diseases, along with the availability of bioinformatics tools capable of handling and integrating large volumes of various types of molecular data at once, offer the possibility of reclassifying these diseases. A new taxonomy could lead to the discovery of new biomarkers for patient stratification and prognosis. Most importantly, this taxonomy might enable important changes in clinical trial design to reach the expected outcomes or the design of molecularly targeted therapies. In this Review, we discuss the basis for a new molecular taxonomy for autoimmune rheumatic diseases. We highlight the evidence surrounding the idea that these diseases share molecular features related to their pathogenesis and development and discuss previous attempts to classify these diseases. We evaluate the tools available to analyse and combine different types of molecular data. Finally, we introduce PRECISESADS, a project aimed at reclassifying the systemic autoimmune diseases.

Pediatric Evans syndrome is associated with a high frequency of potentially damaging variants in immune genes

Evans syndrome (ES) is a rare severe autoimmune disorder characterized by the combination of autoimmune hemolytic anemia and immune thrombocytopenia. In most cases, the underlying cause is unknown. We sought to identify genetic defects in pediatric ES (pES), based on a hypothesis of strong genetic determinism. In a national, prospective cohort of 203 patients with early-onset ES (median [range] age at last follow-up: 16.3 years ([1.2-41.0 years]) initiated in 2004, 80 nonselected consecutive individuals underwent genetic testing. The clinical data were analyzed as a function of the genetic findings. Fifty-two patients (65%) received a genetic diagnosis (the M+ group): 49 carried germline mutations and 3 carried somatic variants. Thirty-two (40%) had pathogenic mutations in 1 of 9 genes known to be involved in primary immunodeficiencies (TNFRSF6, CTLA4, STAT3, PIK3CD, CBL, ADAR1, LRBA, RAG1, and KRAS), whereas 20 patients (25%) carried probable pathogenic variants in 16 genes that had not previously been reported in the context of autoimmune disease. Lastly, no genetic abnormalities were found in the remaining 28 patients (35%, the M- group). The M+ group displayed more severe disease than the M- group, with a greater frequency of additional immunopathologic manifestations and a greater median number of lines of treatment. Six patients (all from the M+ group) died during the study. In conclusion, pES was potentially genetically determined in at least 65% of cases. Systematic, wide-ranging genetic screening should be offered in pES; the genetic findings have prognostic significance and may guide the choice of a targeted treatment.

Identification of Target Genes at Juvenile Idiopathic Arthritis GWAS Loci in Human Neutrophils

Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic disease among children which could cause severe disability. Genomic studies have discovered substantial number of risk loci for JIA, however, the mechanism of how these loci affect JIA development is not fully understood. Neutrophil is an important cell type involved in autoimmune diseases. To better understand the biological function of genetic loci in neutrophils during JIA development, we took an integrated multi-omics approach to identify target genes at JIA risk loci in neutrophils and constructed a protein-protein interaction network via a machine learning approach. We identified genes likely to be JIA risk loci targeted genes in neutrophils which could contribute to JIA development.

Candidate gene analyses for acute pain and morphine analgesia after pediatric day surgery: African American versus European Caucasian ancestry and dose prediction limits

Acute pain and opioid analgesia demonstrate inter-individual variability and polygenic influence. In 241 children of African American and 277 of European Caucasian ancestry, we sought to replicate select candidate gene associations with morphine dose and postoperative pain and then to estimate dose prediction limits. Twenty-seven single-nucleotide polymorphisms (SNPs) from nine genes (ABCB1, ARRB2, COMT, DRD2, KCNJ6, MC1R, OPRD1, OPRM1, and UGT2B7) met selection criteria and were analyzed along with TAOK3. Few associations replicated: morphine dose (mcg/kg) in African American children and ABCB1 rs1045642 (A allele, β = -9.30, 95% CI: -17.25 to -1.35, p = 0.02) and OPRM1 rs1799971 (G allele, β = 23.19, 95% CI: 3.27-43.11, p = 0.02); KCNJ6 rs2211843 and high pain in African American subjects (T allele, OR 2.08, 95% CI: 1.17-3.71, p = 0.01) and in congruent European Caucasian pain phenotypes; and COMT rs740603 for high pain in European Caucasian subjects (A allele, OR: 0.69, 95% CI: 0.48-0.99, p = 0.046). With age, body mass index, and physical status as covariates, simple top SNP candidate gene models could explain theoretical maximums of 24.2% (European Caucasian) and 14.6% (African American) of morphine dose variances.

Exploring Systemic Autoimmunity in Thyroid Disease Subjects

Introduction

Individuals with one autoimmune disease are at risk of developing a second autoimmune disease, but the pathogenesis or the sequential occurrence of multiple autoimmune diseases has not been established yet. In this study, we explored the association and sequential occurrence of antibodies in thyroid disease and systemic autoimmune disease subjects. We evaluated thyroid hormones, thyroid-stimulating hormone (TSH), free thyroxine (FT4), thyroid autoantibodies, anti-thyroperoxidase (anti-TPO), and anti-thyroglobulin (Tg) to comprehend the association with systemic autoimmune autoantibodies, anti-nuclear antibodies (ANA), and autoantibodies to extractable nuclear antigens (ENA) in subjects with thyroid-related symptoms.

Methods

A total of 14825 subjects with thyroid-related symptoms were tested at Vibrant America Clinical Laboratory for thyroid markers (TSH, FT4, anti-TPO, and anti-Tg) and an autoimmune panel (ANA panel and ENA-11 profile) from March 2016 to May 2018. Thyroid-positive (based on TSH and FT4 levels), anti-TPO-positive, and anti-Tg-positive subjects were assessed for the prevalence of ANA and anti-ENA antibodies. A 2-year follow-up study was conducted to assess the sequential order of appearance of autoimmune markers in thyroid and systemic autoimmune diseases.

Results

In the retrospective analysis, 343/1671 (20.5%), 2037/11235 (18.1%), and 1658/9349 (17.7%) of thyroid+, anti-TPO+, and anti-Tg+ subjects were found to be seropositive for ANA. Anti-ENA was detected in a higher prevalence than ANA with 475/1671 (28.4%), 3063/11235 (27.3%), and 2511/9349 (26.9%) in the same groups of subjects, respectively. Our results are found to be much higher than the reported prevalence of anti-ENA in general population. During the 2-year follow-up study, anti-TPO appeared significantly earlier than ANA and anti-ENA in an average of 253 (±139) and 227 (±127) days, respectively.

Conclusions

A high prevalence of anti-ENA and ANA was found to be coexisting with autoimmune thyroid disease subjects, with anti-TPO occurring prior to the onset of ANA and anti-ENA. Therefore, frequent follow-ups and evaluation of ANA and anti-ENA in subjects with anti-TPO positivity would be beneficial in early detection of other systemic autoimmune diseases.

Identification of loci where DNA methylation potentially mediates genetic risk of type 1 diabetes

The risk of Type 1 Diabetes (T1D) comprises both genetic and environmental components. We investigated whether genetic susceptibility to T1D could be mediated by changes in DNA methylation, an epigenetic mechanism that potentially plays a role in autoimmune diabetes. From enrichment analysis, we found that there was a common genetic influence for both DNA methylation and T1D across the genome, implying that methylation could be either on the causal pathway to T1D or a non-causal biomarker of T1D genetic risk. Using data from a general population comprising blood samples taken at birth (n = 844), childhood (n = 846) and adolescence (n = 907), we then evaluated the associations between 64 top GWAS single nucleotide polymorphisms (SNPs) and DNA methylation levels at 55 non-HLA loci. We identified 95 proximal SNP-cytosine phosphate guanine (CpG) pairs (cis) and 1 distal SNP-CpG association (trans) consistently at birth, childhood, and adolescence. Combining genetic co-localization and Mendelian Randomization analysis, we provided evidence that at 5 loci, ITGB3BP, AFF3, PTPN2, CTSH and CTLA4, DNA methylation is potentially mediating the genetic risk of T1D mainly by influencing local gene expression.

Unravelling the Roles of Susceptibility Loci for Autoimmune Diseases in the Post-GWAS Era

Although genome-wide association studies (GWAS) have identified several hundred loci associated with autoimmune diseases, their mechanistic insights are still poorly understood. The human genome is more complex than single nucleotide polymorphisms (SNPs) that are interrogated by GWAS arrays. Apart from SNPs, it also comprises genetic variations such as insertions-deletions, copy number variations, and somatic mosaicism. Although previous studies suggest that common copy number variations do not play a major role in autoimmune disease risk, it is possible that certain rare genetic variations with large effect sizes are relevant to autoimmunity. In addition, other layers of regulations such as gene-gene interactions, epigenetic-determinants, gene and environmental interactions also contribute to the heritability of autoimmune diseases. This review focuses on discussing why studying these elements may allow us to gain a more comprehensive understanding of the aetiology of complex autoimmune traits.

Identification of non-HLA genes associated with development of islet autoimmunity and type 1 diabetes in the prospective TEDDY cohort

Traditional linkage analysis and genome-wide association studies have identified HLA and a number of non-HLA genes as genetic factors for islet autoimmunity (IA) and type 1 diabetes (T1D). However, the relative risk associated with previously identified non-HLA genes is usually very small as measured in cases/controls from mixed populations. Genetic associations for IA and T1D may be more accurately assessed in prospective cohorts. In this study, 5806 subjects from the TEDDY (The Environmental Determinants of Diabetes in the Young) study, an international prospective cohort study, were genotyped for 176,586 SNPs on the ImmunoChip. Cox proportional hazards analyses were performed to discover the SNPs associated with the risk for IA, T1D, or both. Three regions were associated with the risk of developing any persistent confirmed islet autoantibody: one known region near SH2B3 (HR = 1.35, p = 3.58 × 10-7) with Bonferroni-corrected significance and another known region near PTPN22 (HR = 1.46, p = 2.17 × 10-6) and one novel region near PPIL2 (HR = 2.47, p = 9.64 × 10-7) with suggestive evidence (p < 10-5). Two known regions (PTPN22: p = 2.25 × 10-6, INS; p = 1.32 × 10-7) and one novel region (PXK/PDHB: p = 8.99 × 10-6) were associated with the risk for multiple islet autoantibodies. First appearing islet autoantibodies differ with respect to association. Two regions (INS: p = 5.67 × 10-6 and TTC34/PRDM16: 6.45 × 10-6) were associated if the fist appearing autoantibody was IAA and one region (RBFOX1: p = 8.02 × 10-6) was associated if the first appearing autoantibody was GADA. The analysis of T1D identified one region already known to be associated with T1D (INS: p = 3.13 × 10-7) and three novel regions (RNASET2, PLEKHA1, and PPIL2; 5.42 × 10-6 > p > 2.31 × 10-6). These results suggest that a number of low frequency variants influence the risk of developing IA and/or T1D and these variants can be identified by large prospective cohort studies using a survival analysis approach.

Genomics of Systemic Lupus Erythematosus: Insights Gained by Studying Monogenic Young-Onset Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a systemic, autoimmune, multisystem disease with a heterogeneous clinical phenotype. Genome-wide association studies have identified multiple susceptibility loci, but these explain a fraction of the estimated heritability. This is partly because within the broad spectrum of SLE are monogenic diseases that tend to cluster in patients with young age of onset, and in families. This article highlights insights into the pathogenesis of SLE provided by these monogenic diseases. It examines genetic causes of complement deficiency, abnormal interferon production, and abnormalities of tolerance, resulting in monogenic SLE with overlapping clinical features, autoantibodies, and shared inflammatory pathways.

Phenotypic characterization of patients with rheumatologic manifestations of common variable immunodeficiency

Patients with common variable immunodeficiency (CVID) have a higher incidence of rheumatologic disorders. To delineate this clinical association, we investigated the phenotypic features of patients with CVID affected by these conditions.

METHODS

We conducted a retrospective analysis of 870 pediatric and adult patients with CVID included in the United States Immunodeficiency Network (USIDNET) registry. Outcomes included clinical characteristics (age, gender, ethnicity, rheumatologic diagnosis, and comorbidities), infectious history and basic immunophenotype (serum immunoglobulin levels, CD19+ B cells, and CD4/CD8 ratio) in patients with CVID and rheumatologic disorders compared to those with non-inflammatory CVID. Demographic and clinical data were compared using chi-square, Fisher's exact or Wilcoxon-Mann-Whitney tests. Non-parametric tests, single and multiple logistic regression models were used to evaluate the relationship between CVID-associated rheumatologic disorders and basic immunophenotypic parameters (IgA, IgM, CD19+ B-cell counts, and CD4/CD8 ratios).

RESULTS

Physician-reported rheumatic diseases were present in 5.9% of patients with CVID (n = 51) included in the registry. Although CVID affects both sexes equally, and patients are of predominantly White-Caucasian ethnicity, there were more females (3.3:1 female to male ratio) and increased proportion of non-white patients in the rheumatologic disease group (p < 0.05). Specific disorders included: inflammatory arthritis (n = 18), Sjogren's syndrome (n = 11), SLE (n = 8), Raynaud's syndrome (n = 8), vasculitis (n = 9), MCTD (n = 3), and other (n = 5). In about one-third of patients, a rheumatologic condition was associated with an additional inflammatory complication or malignancy. In regards to the immunophenotype parameters compared (CD19+ B-cell counts, CD4/CD8 ratio, IgA, and IgM), no significant differences were demonstrated between the two groups.

CONCLUSION

Our findings highlight the coexistence of primary antibody immunodeficiencies and systemic rheumatologic disorders, describe the spectrum of rheumatologic manifestations, and contrast differences in relevant demographic, clinical and immunophenotype parameters in the largest registry of CVID patients in the U.S. In spite of its limitations, our study details the intersection of systemic autoimmunity and CVID and provides valuable insights into these two groups of disorders. Further delineating the link between systemic autoimmunity and humoral immunodeficiencies can provide novel insights into the immune abnormalities underlying these related conditions.

Impact of autoimmune diseases on outcome of patients with early breast cancer

Our aim was to analyze the impact of a concurrent autoimmune disease on outcome of patients with early breast cancer. We reviewed medical charts of patients with a diagnosis of autoimmune diseases (AD) among a population of 17.153 cases. We categorized ADs as endocrine, rheumatic, systemic, neurological diseases and vasculitis. For each patient in the study group, we matched 2 patients. The events to determine overall survival (OS) and disease free survival (DFS) were identified from follow-up data. We identified 279 (1.62%) patients with early breast cancer and concurrent ADs. The median follow-up was 7.0 years. The 10-year OS rate was 86% (95% CI, 80% to 91%) in the study group and 90% (95% CI, 86% to 93%) for the control group (p = 0.011). In patients with ER positive/HER2 negative subtype a worse OS was observed in the study group when compared to the control group (p = 0.0046); this difference remained statistically significant when the analysis was restricted to breast cancer mortality (p = 0.045). The 10-year DFS rate was 69% (95% CI, 61% to 76%) in the study group and 72% (95% CI, 66% to 77%) for the control group (p = 0.22). Autoimmunity at diagnosis of early breast cancer is associated with worse survival.

GWAS for male-pattern baldness identifies 71 susceptibility loci explaining 38% of the risk

Male pattern baldness (MPB) or androgenetic alopecia is one of the most common conditions affecting men, reaching a prevalence of ~50% by the age of 50; however, the known genes explain little of the heritability. Here, we present the results of a genome-wide association study including more than 70,000 men, identifying 71 independently replicated loci, of which 30 are novel. These loci explain 38% of the risk, suggesting that MPB is less genetically complex than other complex traits. We show that many of these loci contain genes that are relevant to the pathology and highlight pathways and functions underlying baldness. Finally, despite only showing genome-wide genetic correlation with height, pathway-specific genetic correlations are significant for traits including lifespan and cancer. Our study not only greatly increases the number of MPB loci, illuminating the genetic architecture, but also provides a new approach to disentangling the shared biological pathways underlying complex diseases.

The DNA methylation landscape of CD4+ T cells in oligoarticular juvenile idiopathic arthritis

Juvenile idiopathic arthritis (JIA) is presumed to be driven by an adverse combination of genes and environment. Epigenetic processes, including DNA methylation, act as a conduit through which the environment can regulate gene activity. Altered DNA methylation has been associated with adult autoimmune rheumatic diseases such as rheumatoid arthritis, but studies are lacking for paediatric autoimmune rheumatic diseases including JIA. Here, we performed a genome-scale case-control analysis of CD4⁺ T cell DNA methylation from 56 oligoarticular JIA (oJIA) cases and 57 age and sex matched controls using Illumina HumanMethylation450 arrays. DNA methylation at each array probe was tested for association with oJIA using RUV (Remove Unwanted Variation) together with a moderated t-test. Further to this 'all-inclusive' analysis, we stratified by age at diagnosis (≤6yrs, >6yrs) and by sex as potential sources of heterogeneity. Following False Discovery Rate (FDR) adjustment, no probes were associated with oJIA in the all-inclusive, >6yrs-diagnosed, or sex-stratified analyses, and only one probe was associated with oJIA in the ≤6yrs-diagnosed analysis. We attempted technical validation and replication of 14 probes (p_unadj<0.01) at genes of known/potential relevance to disease. At VPS53, we demonstrated a regional shift towards higher methylation in oJIA (all-inclusive) compared to controls. At REEP3, where polymorphism has been previously associated with JIA, we demonstrated higher DNA methylation in male oJIA compared to male controls. This is the most comprehensive JIA case-control analysis of DNA methylation to date. While we have generated some evidence of altered methylation in oJIA, substantial differences are not apparent in CD4⁺ T cells. This may indicate a lesser relevance of DNA methylation levels in childhood, compared to adult, rheumatic disease.

Optimal detection of weak positive latent dependence between two sequences of multiple tests

It is frequently of interest to jointly analyze two paired sequences of multiple tests. This paper studies the problem of detecting whether there are more pairs of tests that are significant in both sequences than would be expected by chance. The asymptotic detection boundary is derived in terms of parameters such as the sparsity of non-null cases in each sequence, the effect sizes of the signals, and the magnitude of the dependence between the two sequences. A new test for detecting weak dependence is also proposed, shown to be asymptotically adaptively optimal, studied in simulations, and applied to study genetic pleiotropy in 10 pediatric autoimmune diseases.

10 Years of GWAS Discovery: Biology, Function, and Translation

Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.

Sequences of 95 human MHC haplotypes reveal extreme coding variation in genes other than highly polymorphic HLA class I and II

The most polymorphic part of the human genome, the MHC, encodes over 160 proteins of diverse function. Half of them, including the HLA class I and II genes, are directly involved in immune responses. Consequently, the MHC region strongly associates with numerous diseases and clinical therapies. Notoriously, the MHC region has been intractable to high-throughput analysis at complete sequence resolution, and current reference haplotypes are inadequate for large-scale studies. To address these challenges, we developed a method that specifically captures and sequences the 4.8-Mbp MHC region from genomic DNA. For 95 MHC homozygous cell lines we assembled, de novo, a set of high-fidelity contigs and a sequence scaffold, representing a mean 98% of the target region. Included are six alternative MHC reference sequences of the human genome that we completed and refined. Characterization of the sequence and structural diversity of the MHC region shows the approach accurately determines the sequences of the highly polymorphic HLA class I and HLA class II genes and the complex structural diversity of complement factor C4A/C4B. It has also uncovered extensive and unexpected diversity in other MHC genes; an example is MUC22, which encodes a lung mucin and exhibits more coding sequence alleles than any HLA class I or II gene studied here. More than 60% of the coding sequence alleles analyzed were previously uncharacterized. We have created a substantial database of robust reference MHC haplotype sequences that will enable future population scale studies of this complicated and clinically important region of the human genome.

Rare phenotypes in the understanding of autoimmunity

The study of rare phenotypes has a long history in the description of autoimmune disorders. First Mendelian syndromes of idiopathic tissue destruction were defined more than 100 years ago and were later revealed to result from immune-mediated reactivity against self. In the past two decades, continuous advances in sequencing technology and particularly the advent of next-generation sequencing have allowed to define the genetic basis of an ever-growing number of Mendelian forms of autoimmunity. This has provided unique insight into the molecular pathways that govern immunological homeostasis and that are indispensable for the prevention of self-reactive immune-mediated tissue damage and 'horror autotoxicus'. Here we will discuss selected examples of past and recent investigations into rare phenotypes of autoimmunity that have delineated pathways critical for central and peripheral control of the adaptive immune system. We will outline the implications of these findings for rare and common forms of autoimmunity and will discuss the benefits and potential pitfalls of the integration of next-generation sequencing into algorithms for clinical diagnostics. Because of the concise nature of this review, we will focus on syndromes caused by defects in the control of adaptive immunity as innate immune-mediated autoinflammatory disorders have been covered in excellent recent reviews on Mendelian and polygenic forms of autoimmunity.

Integrative genetic risk prediction using non-parametric empirical Bayes classification

Genetic risk prediction is an important component of individualized medicine, but prediction accuracies remain low for many complex diseases. A fundamental limitation is the sample sizes of the studies on which the prediction algorithms are trained. One way to increase the effective sample size is to integrate information from previously existing studies. However, it can be difficult to find existing data that examine the target disease of interest, especially if that disease is rare or poorly studied. Furthermore, individual-level genotype data from these auxiliary studies are typically difficult to obtain. This article proposes a new approach to integrative genetic risk prediction of complex diseases with binary phenotypes. It accommodates possible heterogeneity in the genetic etiologies of the target and auxiliary diseases using a tuning parameter-free non-parametric empirical Bayes procedure, and can be trained using only auxiliary summary statistics. Simulation studies show that the proposed method can provide superior predictive accuracy relative to non-integrative as well as integrative classifiers. The method is applied to a recent study of pediatric autoimmune diseases, where it substantially reduces prediction error for certain target/auxiliary disease combinations. The proposed method is implemented in the R package ssa.

Genotype-Phenotype Associations of the CD-Associated Single Nucleotide Polymorphism within the Gene Locus Encoding Protein Tyrosine Phosphatase Non-Receptor Type 22 in Patients of the Swiss IBD Cohort

BACKGROUND

Protein tyrosine phosphatase non-receptor type 22 (PTPN22) plays an important role in immune cell function and intestinal homeostasis. The single nucleotide polymorphism (SNP) rs2476601 within the PTPN22 gene locus results in aberrant function of PTPN22 protein and protects from Crohn's disease (CD). Here, we investigated associations of PTPN22 SNP rs2476601 in inflammatory bowel disease (IBD) patients in the Swiss IBD Cohort Study (SIBDCS).

METHODS

2'028 SIBDCS patients (1173 CD and 855 ulcerative colitis (UC) patients) were included. The clinical characteristics were analysed for an association with the presence of the PTPN22 SNP rs2476601 genotypes 'homozygous variant' (AA), 'heterozygous' (GA) and 'homozygous wild-type' (GG).

RESULTS

13 patients (0.6%) were homozygous variant (AA) for the PTPN22 polymorphism, 269 (13.3%) heterozygous variant (GA) and 1'746 (86.1%) homozygous wild-type (GG). In CD, AA and GA genotypes were associated with less use of steroids and antibiotics, and reduced prevalence of vitamin D and calcium deficiency. In UC the AA and GA genotype was associated with increased use of azathioprine and anti-TNF antibodies, but significantly less patients with the PTPN22 variant featured malabsorption syndrome (p = 0.026).

CONCLUSION

Our study for the first time addressed how presence of SNP rs2476601 within the PTPN22 gene affects clinical characteristics in IBD-patients. Several factors that correlate with more severe disease were found to be less common in CD patients carrying the A-allele, pointing towards a protective role for this variant in affected CD patients. In UC patients however, we found the opposite trend, suggesting a disease-promoting effect of the A-allele.

Understanding the genetic and epigenetic basis of common variable immunodeficiency disorder through omics approaches

BACKGROUND

Common variable immunodeficiency disorder (CVID) is the most frequently encountered symptomatic primary immunodeficiency, characterized by highly heterogeneous immunological features and clinical presentations. As better targeted therapies are importantly needed for CVID, improved understanding of the genetic and epigenetic basis for the development of CVID presents the most promising venue for improvement.

SCOPE OF REVIEW

Several genomic and epigenomic studies of CVID have recently been carried out on cohorts of sporadic cases of CVID. Using high-throughput array and sequencing technologies, these studies identified several loci associated with the disease. Here, we review the omics approaches used in these studies and resulting discoveries. We also discuss how these findings lead to improved understanding of the molecular basis of CVID and possible future directions to pursue.

MAJOR CONCLUSIONS

High-throughput omics approaches have been productive in genetic and epigenetic studies of CVID, leading to the identifications of several significantly associated loci of different variant types, as well as genes and pathways elucidating the shared genetic basis of CVID and autoimmunity. Complex polygenic model of inheritance together with interplay between genetic components and environmental factors may account for the etiology of CVID and various associated comorbidities.

GENERAL SIGNIFICANCE

The genetic and epigenetic basis of CVID when further translated through functional studies will allow for improved understanding of the CVID etiology and will provide new insights into the development of potential new therapeutic approaches for this devastating condition. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Results of the Fifth Scientific Workshop of the ECCO (II): Pathophysiology of Perianal Fistulizing Disease

The fifth scientific workshop of the European Crohn's and Colitis Organization (ECCO) focused on the relevance of fistulas to the disease course of patients with Crohn's disease (CD). The objectives were to reach a better understanding of the pathophysiological mechanisms underlying the formation of CD fistulas; to identify future topics in fistula research that could provide insights into pathogenesis; to develop novel therapeutic approaches; and to review current therapeutic strategies (with clarification of existing approaches to prevention, diagnosis and treatment). The results of the workshop are presented in two separate manuscripts. This manuscript describes current state-of-the-art knowledge about fistula pathogenesis, including the roles of epithelial-to-mesenchymal transition and cytokine matrix remodelling enzymes, and highlights the common association between fistulas and stenosis in CD. The review also considers the possible roles that genetic predisposition and intestinal microbiota play in fistula development. Finally, it proposes future directions and needs for fistula research that might substantially increase our understanding of this complex condition and help unravel novel therapeutic strategies and specific targets for treatment. Overall, it aims to highlight unanswered questions in fistula research and to provide a framework for future research work.