Autoimmune disease classification by inverse association with SNP alleles

Integrative deep learning with prior assisted feature selection

Integrative analysis has emerged as a prominent tool in biomedical research, offering a solution to the "smalln $$ n $$ and largep $$ p $$ " challenge. Leveraging the powerful capabilities of deep learning in extracting complex relationship between genes and diseases, our objective in this study is to incorporate deep learning into the framework of integrative analysis. Recognizing the redundancy within candidate features, we introduce a dedicated feature selection layer in the proposed integrative deep learning method. To further improve the performance of feature selection, the rich previous researches are utilized by an ensemble learning method to identify "prior information". This leads to the proposed prior assisted integrative deep learning (PANDA) method. We demonstrate the superiority of the PANDA method through a series of simulation studies, showing its clear advantages over competing approaches in both feature selection and outcome prediction. Finally, a skin cutaneous melanoma (SKCM) dataset is extensively analyzed by the PANDA method to show its practical application.

Genetic mapping across autoimmune diseases reveals shared associations and mechanisms

Autoimmune and inflammatory diseases are polygenic disorders of the immune system. Many genomic loci harbor risk alleles for several diseases, but the limited resolution of genetic mapping prevents determining whether the same allele is responsible, indicating a shared underlying mechanism. Here, using a collection of 129,058 cases and controls across 6 diseases, we show that ~40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles twofold by combining cases and controls across diseases, allowing us to identify more expression quantitative trait loci driven by the shared alleles. The patterns indicate widespread sharing of pathogenic mechanisms but not a single global autoimmune mechanism. Our approach can be applied to any set of traits and is particularly valuable as sample collections become depleted.

Genetic Basis of Inflammatory Demyelinating Diseases of the Central Nervous System: Multiple Sclerosis and Neuromyelitis Optica Spectrum

Demyelinating diseases alter myelin or the coating surrounding most nerve fibers in the central and peripheral nervous systems. The grouping of human central nervous system demyelinating disorders today includes multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) as distinct disease categories. Each disease is caused by a complex combination of genetic and environmental variables, many involving an autoimmune response. Even though these conditions are fundamentally similar, research into genetic factors, their unique clinical manifestations, and lesion pathology has helped with differential diagnosis and disease pathogenesis knowledge. This review aims to synthesize the genetic approaches that explain the differential susceptibility between these diseases, explore the overlapping clinical features, and pathological findings, discuss existing and emerging hypotheses on the etiology of demyelination, and assess recent pathogenicity studies and their implications for human demyelination. This review presents critical information from previous studies on the disease, which asks several questions to understand the gaps in research in this field.

The Relationship Between Rosacea and Inflammatory Bowel Disease: A Systematic Review and Meta-analysis

INTRODUCTION

Rosacea and inflammatory bowel disease (IBD) are chronic inflammatory disorders of the skin and the gut, which are interfaces between the environment and the human body. Although growing evidence has implicated a possible link between rosacea and IBD, it remains unclear whether IBD increases the risk of rosacea and vice versa. Therefore, we investigated the association between rosacea and IBD in this study.

METHODS

We performed a systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines.

RESULTS

Eight eligible studies were included in this meta-analysis. Overall, the prevalence of rosacea was higher in the IBD group than in the control group, with a pooled odds ratio (OR) of 1.86 (95% confidence interval [CI](1), 1.52-2.26). Both the Crohn's disease and the ulcerative colitis groups had higher prevalences of rosacea than the control group, with ORs of 1.74 (95% CI 1.34-2.28) and 2.00 (95% CI 1.63-2.45), respectively. Compared with those in the control group, the risks of IBD, Crohn's disease, and ulcerative colitis were significantly higher in the rosacea group, with incidence rate ratios of 1.37 (95% CI 1.22-1.53), 1.60 (95% CI 1.33-1.92), and 1.26 (95% CI 1.09-1.45), respectively.

CONCLUSION

Our meta-analysis suggests that IBD is bidirectionally associated with rosacea. Future interdisciplinary studies are needed to better understand the mechanism of interaction between rosacea and IBD .

Identifying shared genetic architecture between rheumatoid arthritis and other conditions: a phenome-wide association study with genetic risk scores

BACKGROUND

Rheumatoid arthritis (RA) shares genetic variants with other autoimmune conditions, but existing studies test the association between RA variants with a pre-defined set of phenotypes. The objective of this study was to perform a large-scale, systemic screen to determine phenotypes that share genetic architecture with RA to inform our understanding of shared pathways.

METHODS

In the UK Biobank (UKB), we constructed RA genetic risk scores (GRS) incorporating human leukocyte antigen (HLA) and non-HLA risk alleles. Phenotypes were defined using groupings of International Classification of Diseases (ICD) codes. Patients with an RA code were excluded to mitigate the possibility of associations being driven by the diagnosis or management of RA. We performed a phenome-wide association study, testing the association between the RA GRS with phenotypes using multivariate generalized estimating equations that adjusted for age, sex, and first five principal components. Statistical significance was defined using Bonferroni correction. Results were replicated in an independent cohort and replicated phenotypes were validated using medical record review of patients.

FINDINGS

We studied n = 316,166 subjects from UKB without evidence of RA and screened for association between the RA GRS and n = 1317 phenotypes. In the UKB, 20 phenotypes were significantly associated with the RA GRS, of which 13 (65%) were immune mediated conditions including polymyalgia rheumatica, granulomatosis with polyangiitis (GPA), type 1 diabetes, and multiple sclerosis. We further identified a novel association in Celiac disease where the HLA and non-HLA alleles had strong associations in opposite directions. Strikingly, we observed that the non-HLA GRS was exclusively associated with greater risk of the validated conditions, suggesting shared underlying pathways outside the HLA region.

INTERPRETATION

This study replicated and identified novel autoimmune phenotypes verified by medical record review that share immune pathways with RA and may inform opportunities for shared treatment targets, as well as risk assessment for conditions with a paucity of genomic data, such as GPA.

FUNDING

This research was funded by the US National Institutes of Health (P30AR072577, R21AR078339, R35GM142879, T32AR007530) and the Harold and DuVal Bowen Fund.

Germline genetic variation and predicting immune checkpoint inhibitor induced toxicity

Immune checkpoint inhibitor (ICI) therapy has revolutionised the treatment of various cancer types. ICIs reinstate T-cell function to elicit an anti-cancer immune response. The resulting immune response can however have off-target effects which manifest as autoimmune type serious immune-related adverse events (irAE) in ~10-55% of patients treated. It is currently challenging to predict both who will experience irAEs and to what severity. Identification of patients at high risk of serious irAE would revolutionise patient care. While the pathogenesis driving irAE development is still unclear, host genetic factors are proposed to be key determinants of these events. This review presents current evidence supporting the role of the host genome in determining risk of irAE. We summarise the spectrum and timing of irAEs following treatment with ICIs and describe currently reported germline genetic variation associated with expression of immuno-modulatory factors within the cancer immunity cycle, development of autoimmune disease and irAE occurrence. We propose that germline genetic determinants of host immune function and autoimmune diseases could also explain risk of irAE development. We also endorse genome-wide association studies of patients being treated with ICIs to identify genetic variants that can be used in polygenic risk scores to predict risk of irAE.

Frequent somatic mosaicism in T lymphocyte subsets in individuals with and without multiple sclerosis

Background

Somatic variants are variations in an individual's genome acquired after the zygotic stadium and result from mitotic errors or not (fully) repaired DNA damage.

Objectives

To investigate whether somatic mosaicism in T lymphocyte subsets is enriched early in multiple sclerosis (MS).

Methods

We identified somatic variants with variant allele fractions ≥1% across the whole exome in CD4⁺ and CD8⁺ T lymphocytes of 21 treatment-naive MS patients with <5 years of disease duration and 16 partially age-matched healthy controls. We investigated the known somatic STAT3 variant p.Y640F in peripheral blood in a larger cohort of 446 MS patients and 259 controls.

Results

All subjects carried 1-142 variants in CD4⁺ or CD8⁺ T lymphocytes. Variants were more common, more abundant, and increased with age in CD8⁺ T lymphocytes. Somatic variants were common in the genes DNMT3A and especially STAT3. Overall, the presence or abundance of somatic variants, including the STAT3 p.Y640F variant, did not differ between MS patients and controls.

Conclusions

Somatic variation in T lymphocyte subsets is widespread in both control individuals and MS patients. Somatic mosaicism in T lymphocyte subsets is not enriched in early MS and thus unlikely to contribute to MS risk, but future research needs to address whether a subset of variants influences disease susceptibility.

Autoimmune Disease Classification Based on PubMed Text Mining

Autoimmune diseases (AIDs) are often co-associated, and about 25% of patients with one AID tend to develop other comorbid AIDs. Here, we employ the power of datamining to predict the comorbidity of AIDs based on their normalized co-citation in PubMed. First, we validate our technique in a test dataset using earlier-reported comorbidities of seven knowns AIDs. Notably, the prediction correlates well with comorbidity (R = 0.91) and validates our methodology. Then, we predict the association of 100 AIDs and classify them using principal component analysis. Our results are helpful in classifying AIDs into one of the following systems: (1) gastrointestinal, (2) neuronal, (3) eye, (4) cutaneous, (5) musculoskeletal, (6) kidneys and lungs, (7) cardiovascular, (8) hematopoietic, (9) endocrine, and (10) multiple. Our classification agrees with experimentally based taxonomy and ranks AID according to affected systems and gender. Some AIDs are unclassified and do not associate well with other AIDs. Interestingly, Alzheimer’s disease correlates well with other AIDs such as multiple sclerosis. Finally, our results generate a network classification of autoimmune diseases based on PubMed text mining and help map this medical universe. Our results are expected to assist healthcare workers in diagnosing comorbidity in patients with an autoimmune disease, and to help researchers in identifying common genetic, environmental, and autoimmune mechanisms.

TNFSF4 is a risk factor for rheumatoid arthritis but not for primary Sjögren's syndrome in the Mexican population

PURPOSE

Rheumatoid arthritis (RA) and primary Sjögren's syndrome (pSS) are autoimmune diseases (ADs) characterized by joint damage and involvement of the salivary glands, respectively. ADs share some susceptibility loci, such as TNFSF4, which is a classical susceptibility gene associated with systemic lupus erythematosus, but its role in RA and pSS is not yet clear. Thus, the aim of this study was to determine whether three TNFSFS4 polymorphisms are associated with RA and pSS.

METHODS

Our case-control study included 500 controls, 459 patients with RA, and 210 patients with pSS from Mexico. TNFSF4 single nucleotide polymorphisms (SNPs) rs1234315C/T, rs2205960G/T, and rs704840T/G were genotyped using TaqMan probes and discrimination allelic assay.

RESULTS

The three TNFSF4 SNPs were associated with susceptibility to RA (rs1234315C/T: odds ratio [OR] 1.4, p = 0.01; rs2205960G/T: OR 1.23, p = 0.03; rs704840T/G: OR 1.24, p = 0.02). An association between TNFSF4 rs1234315C/T and pSS was also observed (OR 1.28, p = 0.04), however, after Bonferroni correction, this association was lost.

CONCLUSION

Our data suggest that TNFSF4 could be a risk factor in RA but not pSS in a Mexican population.

Multitrait GWAS to connect disease variants and biological mechanisms

Genome-wide association studies (GWASs) have uncovered a wealth of associations between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link with biological mechanisms. Our framework incorporates multitrait association mapping along with an investigation of the breakdown of genetic associations into clusters of variants harboring similar multitrait association profiles. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster assignment and the success of drug targets in randomized controlled trials.

Riok3 inhibits the antiviral immune response by facilitating TRIM40-mediated RIG-I and MDA5 degradation

The type I interferon (IFN) pathway is a key component of innate immune response upon invasion of foreign pathogens. It is also under precise control to prevent excessive upregulation and undesired inflammation cascade. In the present study, we report that Riok3, an atypical kinase, negatively regulates retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) sensing-induced type I IFN signaling. Riok3 deficiency selectively inhibits RNA viral replication in vitro, resulting from an upregulated type I IFN pathway. Mice with myeloid-specific Riok3 knockout also show a more robust induction of type I IFN upon RNA virus infection and are more resistant to RNA virus-induced pathogenesis. Mechanistically, Riok3 recruits and interacts with the E3 ubiquitin ligase TRIM40, leading to the degradation of RIG-I and melanoma differentiation-associated gene-5 (MDA5) via K48- and K27-linked ubiquitination. Collectively, our data reveal the mechanism that Riok3 employs to be a negative regulator of antiviral innate immunity.

Type 1 Diabetes and the HLA Region: Genetic Association Besides Classical HLA Class II Genes

Type 1 diabetes is an autoimmune disease with rising incidence in high-income countries. Genetic and environmental predisposing factors contribute to the etiology of the disease, although their interaction is not sufficiently understood to allow for preventive action. Strongest known associations with genetic variation map to classical HLA class II genes. Because of its genetic complexity, the HLA region has been under-represented in genome-wide association studies, having potentially hindered the identification of relevant associations underlying the etiology of the disease. Here, we performed a comprehensive HLA-wide genetic association analysis of type 1 diabetes including multi-allelic and rare variants. We used high-density whole-exome sequencing data of the HLA region in the large UK Biobank dataset to apply gene-based association tests with a carefully defined type 1 diabetes phenotype (97 cases and 48,700 controls). Exon-based and single-variant association tests were used to complement the analysis. We replicated the known association of type 1 diabetes with the classical HLA-DQ gene. Tailoring the analysis toward rare variants, we additionally identified the lysine methyl transferase EHMT2 as associated. Deeper insight into genetic variation associated with disease as presented and discussed in detail here can help unraveling mechanistic details of the etiology of type 1 diabetes. More specifically, we hypothesize that genetic variation in EHMT2 could impact autoimmunity in type 1 diabetes development.

Emerging Roles of MHC Class I Region-Encoded E3 Ubiquitin Ligases in Innate Immunity

The major histocompatibility complex (MHC) class I (MHC-I) region contains a multitude of genes relevant to immune response. Multiple E3 ubiquitin ligase genes, including tripartite motif 10 (TRIM10), TRIM15, TRIM26, TRIM27, TRIM31, TRIM38, TRIM39, TRIM40, and RING finger protein 39 (RNF39), are organized in a tight cluster, and an additional two TRIM genes (namely TRIM38 and TRIM27) telomeric of the cluster within the MHC-I region. The E3 ubiquitin ligases encoded by these genes possess important roles in controlling the intensity of innate immune responses. In this review, we discuss the E3 ubiquitin ligases encoded within the MHC-I region, highlight their regulatory roles in innate immunity, and outline their potential functions in infection, inflammatory and autoimmune diseases.

Advances in Genomic Discovery and Implications for Personalized Prevention and Medicine: Estonia as Example

The current paradigm of personalized medicine envisages the use of genomic data to provide predictive information on the health course of an individual with the aim of prevention and individualized care. However, substantial efforts are required to realize the concept: enhanced genetic discoveries, translation into intervention strategies, and a systematic implementation in healthcare. Here we review how further genetic discoveries are improving personalized prediction and advance functional insights into the link between genetics and disease. In the second part we give our perspective on the way these advances in genomic research will transform the future of personalized prevention and medicine using Estonia as a primer.

Decoding Neuromuscular Disorders Using Phenotypic Clusters Obtained From Co-Occurrence Networks

Neuromuscular disorders (NMDs) represent an important subset of rare diseases associated with elevated morbidity and mortality whose diagnosis can take years. Here we present a novel approach using systems biology to produce functionally-coherent phenotype clusters that provide insight into the cellular functions and phenotypic patterns underlying NMDs, using the Human Phenotype Ontology as a common framework. Gene and phenotype information was obtained for 424 NMDs in OMIM and 126 NMDs in Orphanet, and 335 and 216 phenotypes were identified as typical for NMDs, respectively. ‘Elevated serum creatine kinase’ was the most specific to NMDs, in agreement with the clinical test of elevated serum creatinine kinase that is conducted on NMD patients. The approach to obtain co-occurring NMD phenotypes was validated based on co-mention in PubMed abstracts. A total of 231 (OMIM) and 150 (Orphanet) clusters of highly connected co-occurrent NMD phenotypes were obtained. In parallel, a tripartite network based on phenotypes, diseases and genes was used to associate NMD phenotypes with functions, an approach also validated by literature co-mention, with KEGG pathways showing proportionally higher overlap than Gene Ontology and Reactome. Phenotype-function pairs were crossed with the co-occurrent NMD phenotype clusters to obtain 40 (OMIM) and 72 (Orphanet) functionally coherent phenotype clusters. As expected, many of these overlapped with known diseases and confirmed existing knowledge. Other clusters revealed interesting new findings, indicating informative phenotypes for differential diagnosis, providing deeper knowledge of NMDs, and pointing towards specific cell dysfunction caused by pleiotropic genes. This work is an example of reproducible research that i) can help better understand NMDs and support their diagnosis by providing a new tool that exploits existing information to obtain novel clusters of functionally-related phenotypes, and ii) takes us another step towards personalised medicine for NMDs.

Genetic risk factors for autoimmune hepatitis: implications for phenotypic heterogeneity and biomarkers for drug response

Autoimmune hepatitis (AIH) is a rare chronic progressive liver disease with autoimmune features. It mainly affects middle-aged women. AIH is occasionally complicated with liver cirrhosis that worsens the prognosis. Genetic and environmental factors are involved in the pathogenesis of AIH. Genetic studies of other diseases have been revealing of pathogenesis and drug efficacy. In this review, we summarize the genetic risk factors for AIH, including human leukocyte antigen (HLA) and non-HLA genes. A genome-wide association study (GWAS) on European AIH revealed the strongest associations to be with single nucleotide variants (SNVs) in HLA. Predisposing alleles for AIH were DRB1*03:01 and DRB1*04:01 in Europeans; DRB1*04:04, DRB1*04:05, and DRB1*13:01 in Latin Americans; and DRB1*04:01 and DRB1*04:05 in Japanese. Other risk SNVs in non-HLA genes for AIH were found by a candidate gene approach, but several SNVs were confirmed in replication studies. Some genetic factors of AIH overlapped with those of other autoimmune diseases. Larger-scale GWASs of other ethnic groups are required. The results of genetic studies might provide an explanation for the phenotypic heterogeneity of AIH and biomarkers for drug responses.

Association of Vitamin D Metabolism Gene Polymorphisms with Autoimmunity: Evidence in Population Genetic Studies

A high prevalence of vitamin D (calcidiol) serum deficiency has been described in several autoimmune diseases, including multiple sclerosis (MS), rheumatoid arthritis (AR), and systemic lupus erythematosus (SLE). Vitamin D is a potent immunonutrient that through its main metabolite calcitriol, regulates the immunomodulation of macrophages, dendritic cells, T and B lymphocytes, which express the vitamin D receptor (VDR), and they produce and respond to calcitriol. Genetic association studies have shown that up to 65% of vitamin D serum variance may be explained due to genetic background. The 90% of genetic variability takes place in the form of single nucleotide polymorphisms (SNPs), and SNPs in genes related to vitamin D metabolism have been linked to influence the calcidiol serum levels, such as in the vitamin D binding protein (VDBP; rs2282679 GC), 25-hydroxylase (rs10751657 CYP2R1), 1α-hydroxylase (rs10877012, CYP27B1) and the vitamin D receptor (FokI (rs2228570), BsmI (rs1544410), ApaI (rs7975232), and TaqI (rs731236) VDR). Therefore, the aim of this comprehensive literature review was to discuss the current findings of functional SNPs in GC, CYP2R1, CYP27B1, and VDR associated to genetic risk, and the most common clinical features of MS, RA, and SLE.

Epigenetic modification and therapeutic targets of diabetes mellitus

The prevalence of diabetes and its related complications are increasing significantly globally. Collected evidence suggested that several genetic and environmental factors contribute to diabetes mellitus. Associated complications such as retinopathy, neuropathy, nephropathy and other cardiovascular complications are a direct result of diabetes. Epigenetic factors include deoxyribonucleic acid (DNA) methylation and histone post-translational modifications. These factors are directly related with pathological factors such as oxidative stress, generation of inflammatory mediators and hyperglycemia. These result in altered gene expression and targets cells in the pathology of diabetes mellitus without specific changes in a DNA sequence. Environmental factors and malnutrition are equally responsible for epigenetic states. Accumulated evidence suggested that environmental stimuli alter the gene expression that result in epigenetic changes in chromatin. Recent studies proposed that epigenetics may include the occurrence of 'metabolic memory' found in animal studies. Further study into epigenetic mechanism might give us new vision into the pathogenesis of diabetes mellitus and related complication thus leading to the discovery of new therapeutic targets. In this review, we discuss the possible epigenetic changes and mechanism that happen in diabetes mellitus type 1 and type 2 separately. We highlight the important epigenetic and non-epigenetic therapeutic targets involved in the management of diabetes and associated complications.

Revisiting nonclassical HLA II functions in antigen presentation: Peptide editing and its modulation

The nonclassical major histocompatibility complex of class II molecules (ncMHCII) HLA-DM (DM) and HLA-DO (DO) feature essential functions for the selection of the peptides that are displayed by classical MHCII proteins (MHCII) for CD4⁺ T_h cell surveillance. Thus, although the binding groove of classical MHCII dictates the main features of the peptides displayed, ncMHCII function defines the preferential loading of peptides from specific cellular compartments and the extent to which they are presented. DM acts as a chaperone for classical MHCII molecules facilitating peptide exchange and thereby favoring the binding of peptide-MHCII complexes of high kinetic stability mostly in late endosomal compartments. DO on the other hand binds to DM blocking its peptide-editing function in B cells and thymic epithelial cells, limiting DM activity in these cellular subsets. DM and DO distinct expression patterns therefore define specific antigen presentation profiles that select unique peptide pools for each set of antigen presenting cell. We have come a long way understanding the mechanistic underpinnings of such distinct editing profiles and start to grasp the implications for ncMHCII biological function. DM acts as filter for the selection of immunodominant, pathogen-derived epitopes while DO blocks DM activity under certain physiological conditions to promote tolerance to self. Interestingly, recent findings have shown that the unexplored and neglected ncMHCII genetic diversity modulates retroviral infection in mouse, and affects human ncMHCII function. This review aims at highlighting the importance of ncMHCII function for CD4⁺ T_h cell responses while integrating and evaluating what could be the impact of distinct editing profiles because of natural genetic variations.

Pleiotropy in the Genetic Predisposition to Rheumatoid Arthritis: A Phenome-Wide Association Study and Inverse Variance-Weighted Meta-Analysis

OBJECTIVE

This study was undertaken to investigate the hypothesis that a genetic predisposition toward rheumatoid arthritis (RA) increases the risk of 10 cardiometabolic and autoimmune disorders previously associated with RA in epidemiologic studies, and to define new genetic pleiotropy present in RA.

METHODS

Two approaches were used to test our hypothesis. First, we constructed a weighted genetic risk score (wGRS) and then examined its association with 10 prespecified disorders. Additionally, a phenome-wide association study (PheWAS) was carried out to identify potential new associations. Second, inverse variance-weighted regression (IVWR) meta-analysis was used to characterize the association between genetic susceptibility to RA and the prespecified disorders, with the results expressed as odds ratios (ORs) and 95% confidence intervals (95% CIs).

RESULTS

The wGRS for RA was significantly associated with type 1 diabetes mellitus (DM) (OR 1.10 [95% CI 1.04-1.16]; P = 9.82 × 10^-4 ) and multiple sclerosis (OR 0.82 [95% CI 0.77-0.88]; P = 1.73 × 10^-8 ), but not with other cardiometabolic phenotypes. In the PheWAS, wGRS was also associated with an increased risk of several autoimmune phenotypes including RA, thyroiditis, and systemic sclerosis, and with a decreased risk of demyelinating disorders. In the IVWR meta-analyses, RA was significantly associated with an increased risk of type 1 DM (P = 1.15 × 10^-14 ), with evidence of horizontal pleiotropy (Mendelian Randomization-Egger intercept estimate P = 0.001) likely driven by rs2476601, a PTPN22 variant. The association between type 1 DM and RA remained significant (P = 9.53 × 10^-9 ) after excluding rs2476601, with no evidence of horizontal pleiotropy (intercept estimate P = 0.939). RA was also significantly associated with type 2 DM and C-reactive protein levels. These associations were driven by variation in the major histocompatibility complex region.

CONCLUSION

This study presents evidence of pleiotropy between the genetic predisposition to RA and associated phenotypes found in other autoimmune and cardiometabolic disorders, including type 1 DM.

Data Integration for Immunology

Over the last several years, next-generation sequencing and its recent push toward single-cell resolution have transformed the landscape of immunology research by revealing novel complexities about all components of the immune system. With the vast amounts of diverse data currently being generated, and with the methods of analyzing and combining diverse data improving as well, integrative systems approaches are becoming more powerful. Previous integrative approaches have combined multiple data types and revealed ways that the immune system, both as a whole and as individual parts, is affected by genetics, the microbiome, and other factors. In this review, we explore the data types that are available for studying immunology with an integrative systems approach, as well as the current strategies and challenges for conducting such analyses.

Candidate gene associations reveal sex-specific Graves' disease risk alleles among Chinese Han populations

BACKGROUND

With several susceptibility single nucleotide polymorphisms identified by case-control association studies, Graves' disease is one of the most common forms of autoimmune thyroid disease. In this study, we aimed to determine whether any observed differences in genetic associations are influenced by sex in Chinese Han populations.

METHODS

A total of 8,835 patients with Graves' disease and 9,936 sex-matched healthy controls were enrolled in the study. Confirmed by a two-staged association analysis, sex-specific analyses among 20 Graves' disease susceptibility loci were conducted.

RESULTS

A significant sex-gene interaction was detected primarily at rs5912838 on Xq21.1 between the GPR174 and ITM2A genes, whereby male Graves' disease patients possessed a significantly higher frequency of risk alleles than their female counterparts. Interestingly, compared to women, male patients with Graves' disease had a higher cumulative genetic risk and higher persistent thyroid stimulating hormone receptor antibody-positive rate after receiving antithyroid drug therapy for at least 1 year.

CONCLUSION

The findings of this study suggest the existence of one potential sex-specific Graves' disease variant on Xq21.1. This could increase our understanding of the pivotal mechanism behind Graves' disease and ultimately aid in identifying possible therapeutic targets.

Risk of neuroinflammatory events in arthritis patients treated with tumour necrosis factor alpha inhibitors: a collaborative population-based cohort study from Denmark and Sweden

Objectives

To investigate whether tumour necrosis factor alpha inhibitors (TNFis) are associated with an increased risk of neuroinflammatory diseases among patients with arthritic diseases.

Methods

Cohorts of patients with rheumatoid arthritis (RA, n=25 796), psoriatic arthritis (PsA, n=8586) and ankylosing spondylitis (AS, n=9527) who initiated a TNFi treatment year 2000–2017 were identified from nationwide clinical rheumatology registers in Sweden and Denmark. Information on demyelinating disease and inflammatory neuropathy diagnoses was retrieved from prospective linkage to National Patients Register. A Cox proportional hazard model was used to estimate HRs and 95% CI comparing TNFi exposed and non-exposed, by disease and country.

Results

Among 111 455 patients with RA, we identified 270 (Sweden) and 51 (Denmark) events (all types of neuroinflammatory diseases combined), corresponding to crude incidence rates (per 1000 person-years) of 0.37 (Sweden) and 0.39 (Denmark) in TNFi-treated patients vs 0.39 (Sweden) and 0.28 (Denmark) in unexposed patients, and an age-sex-calendar-period-adjusted HR (95% CI) of 0.97 (0.72 to 1.33) (Sweden) and 1.45 (0.74 to 2.81) (Denmark) in TNFi exposed compared with non-exposed patients. For a total of 64 065 AS/PsA patients, the corresponding numbers were: 196 and 32 events, crude incidence rates of 0.59 and 0.87 in TNFi-treated patients vs 0.40 and 0.19 in unexposed patients, and HRs of 1.50 (1.07 to 2.11) and 3.41 (1.30 to 8.96), for Sweden and Denmark, respectively. For multiple sclerosis, the patterns of HRs were similar.

Conclusions

Use of TNFi in AS/PsA, but not in RA, was associated with increased risk of incident neuroinflammatory disease, though the absolute risk was below one in 1000 patients/year.

Identification of 67 Pleiotropic Genes Associated With Seven Autoimmune/Autoinflammatory Diseases Using Multivariate Statistical Analysis

Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery, this univariate approach has limitations in detecting complex genotype-phenotype correlations. Multivariate analysis is essential to identify shared genetic risk factors acting through common biological mechanisms of autoimmune/autoinflammatory diseases. In this study, GWAS summary statistics, including 41,274 single nucleotide polymorphisms (SNPs) located in 11,516 gene regions, were analyzed to identify shared variants of seven autoimmune/autoinflammatory diseases using the metaCCA method. Gene-based association analysis was used to refine the pleiotropic genes. In addition, GO term enrichment analysis and protein-protein interaction network analysis were applied to explore the potential biological functions of the identified genes. A total of 4,962 SNPs (P < 1.21 × 10-6) and 1,044 pleotropic genes (P < 4.34 × 10-6) were identified by metaCCA analysis. By screening the results of gene-based P-values, we identified the existence of 27 confirmed pleiotropic genes and highlighted 40 novel pleiotropic genes that achieved statistical significance in the metaCCA analysis and were also associated with at least one autoimmune/autoinflammatory in the VEGAS2 analysis. Using the metaCCA method, we identified novel variants associated with complex diseases incorporating different GWAS datasets. Our analysis may provide insights for the development of common therapeutic approaches for autoimmune/autoinflammatory diseases based on the pleiotropic genes and common mechanisms identified.

Horizontal and vertical integrative analysis methods for mental disorders omics data

In recent biomedical studies, omics profiling has been extensively conducted on various types of mental disorders. In most of the existing analyses, a single type of mental disorder and a single type of omics measurement are analyzed. In the study of other complex diseases, integrative analysis, both vertical and horizontal integration, has been conducted and shown to bring significantly new insights into disease etiology, progression, biomarkers, and treatment. In this article, we showcase the applicability of integrative analysis to mental disorders. In particular, the horizontal integration of bipolar disorder and schizophrenia and the vertical integration of gene expression and copy number variation data are conducted. The analysis is based on the sparse principal component analysis, penalization, and other advanced statistical techniques. In data analysis, integration leads to biologically sensible findings, including the disease-related gene expressions, copy number variations, and their associations, which differ from the “benchmark” analysis. Overall, this study suggests the potential of integrative analysis in mental disorder research.

Exploration of shared genetic susceptibility loci between type 1 diabetes and rheumatoid arthritis in the Pakistani population

OBJECTIVE

Type 1 diabetes (T1D) and rheumatoid arthritis (RA) are autoimmune diseases. It is known that certain genetic loci and factors that increase the overall autoimmunity risk can be shared among different autoimmune diseases. We sought to replicate seven T1D-related SNPs (single nucleotide polymorphisms) that have been previously reported to be associated with RA susceptibility in a small set of mixed family-based and case-control Pakistani sample in a relatively large and independent RA case-control sample from the same population. Seven T1D-associated SNPs (GLIS3/rs7020673, BACH2/rs11755527, SKAP2/rs7804356, GDSMB/rs2290400, C6orf173/rs9388489, LOC399716/rs947474 and DLK1-MEG2/rs941576) were genotyped in a large Pakistani RA case-control sample (n = 1959) using TaqMan^® SNP genotyping assays.

RESULTS

None of the tested SNPs showed statistically significant association with RA susceptibility; however, one SNP (GLIS3/rs7020673) showed a trend for association (OR = 0.88, p = 7.99E-02). Our study has failed to replicate the previously reported association of seven T1D-associated SNPs with RA risk in a large sample from the same population. Thus, our results do not support a major role of these T1D SNPs in affecting RA susceptibility in the Pakistani population.

Comparative analysis of gene expression profiles in children with type 1 diabetes mellitus

Type 1 diabetes (T1D) is an autoimmune disease that is typically diagnosed in children. The aim of the present study was to identify potential genes involved in the pathogenesis of childhood T1D. Two datasets of mRNA expression in children with T1D were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) in children with T1D were identified. Functional analysis was performed and a protein‑protein interaction (PPI) network was constructed, as was a transcription factor (TF)‑target network. The expression of selected DEGs was further assessed using reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) analysis. Electronic validation and diagnostic value analysis of the identified DEGs [cytokine inducible SH2 containing protein (CISH), SR‑related CTD associated factor 11 (SCAF11), estrogen receptor 1 (ESR1), Rho GTPase activating protein 25 (ARHGAP25), major histocompatibility complex, class II, DR β4 (HLA‑DRB4) and interleukin 23 subunit α (IL23A)] was performed in the GEO dataset. Compared with the normal control group, a total of 1,467 DEGs with P<0.05 were identified in children with T1D. CISH and SCAF11 were determined to be the most up‑ and downregulated genes, respectively. Heterogeneous nuclear ribonucleoprotein D (HNRNPD; degree=33), protein kinase AMP‑activated catalytic subunit α1 (PRKAA1; degree=11), integrin subunit α4 (ITGA4; degree=8) and ESR1 (degree=8) were identified in the PPI network as high‑degree genes. ARHGAP25 (degree=12), HNRNPD (degree=10), HLA‑DRB4 (degree=10) and IL23A (degree=9) were high‑degree genes identified in the TF‑target network. RT‑qPCR revealed that the expression of HNRNPD, PRKAA1, ITGA4 and transporter 2, ATP binding cassette subfamily B member was consistent with the results of the integrated analysis. Furthermore, the results of the electronic validation were consistent with the bioinformatics analysis. SCAF11, CISH and ARHGAP25 were identified to possess value as potential diagnostic markers for children with T1D. In conclusion, identifying DEGs in children with T1D may contribute to our understanding of its pathogenesis, and such DEGs may be used as diagnostic biomarkers for children with T1D.

Enabling precision medicine in neonatology, an integrated repository for preterm birth research

Preterm birth, or the delivery of an infant prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. In the last decade, the advent and continued development of molecular profiling technologies has enabled researchers to generate vast amount of 'omics' data, which together with integrative computational approaches, can help refine the current knowledge about disease mechanisms, diagnostics, and therapeutics. Here we describe the March of Dimes' Database for Preterm Birth Research (http://www.immport.org/resources/mod), a unique resource that contains a variety of 'omics' datasets related to preterm birth. The database is open publicly, and as of January 2018, links 13 molecular studies with data across tens of thousands of patients from 6 measurement modalities. The data in the repository are highly diverse and include genomic, transcriptomic, immunological, and microbiome data. Relevant datasets are augmented with additional molecular characterizations of almost 25,000 biological samples from public databases. We believe our data-sharing efforts will lead to enhanced research collaborations and coordination accelerating the overall pace of discovery in preterm birth research.

The E3 Ubiquitin Ligase TRIM40 Attenuates Antiviral Immune Responses by Targeting MDA5 and RIG-I

Retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs), including melanoma differentiation-associated gene 5 (MDA5) and RIG-I, are crucial for host recognition of non-self RNAs, especially viral RNA. Thus, the expression and activation of RLRs play fundamental roles in eliminating the invading RNA viruses and maintaining immune homeostasis. However, how RLR expression is tightly regulated remains to be further investigated. In this study, we identified a major histocompatibility complex (MHC)-encoded gene, tripartite interaction motif 40 (TRIM40), as a suppressor of RLR signaling by directly targeting MDA5 and RIG-I. TRIM40 binds to MDA5 and RIG-I and promotes their K27- and K48-linked polyubiquitination via its E3 ligase activity, leading to their proteasomal degradation. TRIM40 deficiency enhances RLR-triggered signaling. Consequently, TRIM40 deficiency greatly enhances antiviral immune responses and decreases viral replication in vivo. Thus, we demonstrate that TRIM40 limits RLR-triggered innate activation, suggesting TRIM40 as a potential therapeutic target for the control of viral infection.

No excess of autoimmune diseases in multiple sclerosis families from the Netherlands

OBJECTIVES

Autoimmune diseases (AIDs) cluster in families; however, to what extent AIDs co-occur in MS multiplex families with two or more affected individuals is still controversial. The study aimed to evaluate coexisting AIDs in this type of families from the Netherlands.

MATERIALS AND METHODS

A total of 155 MS multiplex families (155 MS probands, 959 first-degree relatives and 212 spouses) were characterized for a history of 11 AIDs by means of a self-administered questionnaire.

RESULTS

In 43.2% of MS multiplex families, at least one AID was present in the first-degree relatives. Overall, the frequency of AIDs was not significantly different between patients with MS (11%), their first-degree family members (11%) and controls (5.2%). After correction for age at inclusion and gender, the odds ratios (OR) for AIDs were not significant for patients with MS (OR = 1.8 [0.77-4.34], P = .17) and first-degree family members (OR = 2.0 [0.98-4.10], P = .06) when both compared to spouses. The frequency of AIDs in mothers did not differ from that in fathers after correction for sex bias (19% vs 8%, P = .51). A presence of AID was more often reported in maternal than paternal second-degree relatives (23% vs 10%, P = .0020).

CONCLUSION

Although nearly half of the Dutch MS multiplex families reported an AID, no excess of AIDs was present in patients with MS from multiplex families or their first-degree family members compared to the spouses.

Bivariate Genome-Wide Association Study of Depressive Symptoms With Type 2 Diabetes and Quantitative Glycemic Traits

OBJECTIVE

Shared genetic background may explain phenotypic associations between depression and Type 2 diabetes (T2D). We aimed to study, on a genome-wide level, if genetic correlation and pleiotropic loci exist between depressive symptoms and T2D or glycemic traits.

METHODS

We estimated single-nucleotide polymorphism (SNP)-based heritability and analyzed genetic correlation between depressive symptoms and T2D and glycemic traits with the linkage disequilibrium score regression by combining summary statistics of previously conducted meta-analyses for depressive symptoms by CHARGE consortium (N = 51,258), T2D by DIAGRAM consortium (N = 34,840 patients and 114,981 controls), fasting glucose, fasting insulin, and homeostatic model assessment of β-cell function and insulin resistance by MAGIC consortium (N = 58,074). Finally, we investigated pleiotropic loci using a bivariate genome-wide association study approach with summary statistics from genome-wide association study meta-analyses and reported loci with genome-wide significant bivariate association p value (p < 5 × 10). Biological annotation and function of significant pleiotropic SNPs were assessed in several databases.

RESULTS

The SNP-based heritability ranged from 0.04 to 0.10 in each individual trait. In the linkage disequilibrium score regression analyses, depressive symptoms showed no significant genetic correlation with T2D or glycemic traits (p > 0.37). However, we identified pleiotropic genetic variations for depressive symptoms and T2D (in the IGF2BP2, CDKAL1, CDKN2B-AS, and PLEKHA1 genes), and fasting glucose (in the MADD, CDKN2B-AS, PEX16, and MTNR1B genes).

CONCLUSIONS

We found no significant overall genetic correlations between depressive symptoms, T2D, or glycemic traits suggesting major differences in underlying biology of these traits. However, several potential pleiotropic loci were identified between depressive symptoms, T2D, and fasting glucose, suggesting that previously established phenotypic associations may be partly explained by genetic variation in these specific loci.

Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles

Due to genetic heterogeneity and variable diagnostic criteria, genetic studies of polycystic ovary syndrome are particularly challenging. Furthermore, lack of sufficiently large cohorts limits the identification of susceptibility genes contributing to polycystic ovary syndrome. Here, we carried out a systematic search of studies deposited in the Gene Expression Omnibus database through August 31, 2016. The present analyses included studies with: 1) patients with polycystic ovary syndrome and normal controls, 2) gene expression profiling of messenger RNA, and 3) sufficient data for our analysis. Ultimately, a total of 9 studies with 13 datasets met the inclusion criteria and were performed for the subsequent integrated analyses. Through comprehensive analyses, there were 13 genetic factors overlapped in all datasets and identified as significant specific genes for polycystic ovary syndrome. After quality control assessment, there were six datasets remained. Further gene ontology enrichment and pathway analyses suggested that differentially expressed genes mainly enriched in oocyte pathways. These findings provide potential molecular markers for diagnosis and prognosis of polycystic ovary syndrome, and need in-depth studies on the exact function and mechanism in polycystic ovary syndrome.

HLA and non-HLA genes and familial predisposition to autoimmune diseases in families with a child affected by type 1 diabetes

Genetic predisposition could be assumed to be causing clustering of autoimmunity in individuals and families. We tested whether HLA and non-HLA loci associate with such clustering of autoimmunity. We included 1,745 children with type 1 diabetes from the Finnish Pediatric Diabetes Register. Data on personal or family history of autoimmune diseases were collected with a structured questionnaire and, for a subset, with a detailed search for celiac disease and autoimmune thyroid disease. Children with multiple autoimmune diseases or with multiple affected first- or second-degree relatives were identified. We analysed type 1 diabetes related HLA class II haplotypes and genotyped 41 single nucleotide polymorphisms (SNPs) outside the HLA region. The HLA-DR4-DQ8 haplotype was associated with having type 1 diabetes only whereas the HLA-DR3-DQ2 haplotype was more common in children with multiple autoimmune diseases. Children with multiple autoimmune diseases showed nominal association with RGS1 (rs2816316), and children coming from an autoimmune family with rs11711054 (CCR3-CCR5). In multivariate analyses, the overall effect of non-HLA SNPs on both phenotypes was evident, associations with RGS1 and CCR3-CCR5 region were confirmed and additional associations were implicated: NRP1, FUT2, and CD69 for children with multiple autoimmune diseases. In conclusion, HLA-DR3-DQ2 haplotype and some non-HLA SNPs contribute to the clustering of autoimmune diseases in children with type 1 diabetes and in their families.

Human leukocyte Antigen-DM polymorphisms in autoimmune diseases

Classical MHC class II (MHCII) proteins present peptides for CD4⁺ T-cell surveillance and are by far the most prominent risk factor for a number of autoimmune disorders. To date, many studies have shown that this link between particular MHCII alleles and disease depends on the MHCII's particular ability to bind and present certain peptides in specific physiological contexts. However, less attention has been paid to the non-classical MHCII molecule human leucocyte antigen-DM, which catalyses peptide exchange on classical MHCII proteins acting as a peptide editor. DM function impacts the presentation of both antigenic peptides in the periphery and key self-peptides during T-cell development in the thymus. In this way, DM activity directly influences the response to pathogens, as well as mechanisms of self-tolerance acquisition. While decreased DM editing of particular MHCII proteins has been proposed to be related to autoimmune disorders, no experimental evidence for different DM catalytic properties had been reported until recently. Biochemical and structural investigations, together with new animal models of loss of DM activity, have provided an attractive foundation for identifying different catalytic efficiencies for DM allotypes. Here, we revisit the current knowledge of DM function and discuss how DM function may impart autoimmunity at the organism level.

HLA-DMB restricts human T-cell leukemia virus type-1 (HTLV-1) protein expression via regulation of ATG7 acetylation

The roles of autophagy in viral infection are complicated. While autophagy has been shown to function in host antiviral defense by eliminating intracellular viruses and regulating adaptive immunity, several viruses have evolved molecular mechanisms to get benefits from it. The deltaretrovirus human T-cell leukemia virus type-1 (HTLV-1) has been reported to profit its replication from enhancing autophagosome accumulation. Here, we reported that HLA-DMB (generally referred to here as DMB), the beta chain of the non-classical MHC-II protein HLA-DM, had strong expression in HTLV-1-transformed T-cell lines and could be induced in Hela, PMA-differentiated THP1 (PMA-THP1) or primary human monocytes by HTLV-1 infection. Immunoblot and real-time PCR assays demonstrated that overexpression of DMB decreased HTLV-1 protein expression while the knockdown of DMB increased HTLV-1 protein expression. Immunoblot and confocal microscopy assays indicated that overexpression of DMB decreased HTLV-1 induced autophagosome accumulation while the knockdown of DMB yielded the opposite effects. Coimmunoprecipitation and immunoprecipitation experiments suggested DMB interacted with autophagy-related gene (ATG) 7 and increased the acetylation of ATG7. Taken together, these results suggested DMB modulated HTLV-1 protein expression through regulation of autophagosome accumulation and our findings suggested a new mechanism by which the host cells defended against HTLV-1 infection.

A functional genomics predictive network model identifies regulators of inflammatory bowel disease

A major challenge in inflammatory bowel disease (IBD) is the integration of diverse IBD data sets to construct predictive models of IBD. We present a predictive model of the immune component of IBD that informs causal relationships among loci previously linked to IBD through genome-wide association studies (GWAS) using functional and regulatory annotations that relate to the cells, tissues, and pathophysiology of IBD. Our model consists of individual networks constructed using molecular data generated from intestinal samples isolated from three populations of patients with IBD at different stages of disease. We performed key driver analysis to identify genes predicted to modulate network regulatory states associated with IBD, prioritizing and prospectively validating 12 of the top key drivers experimentally. This validated key driver set not only introduces new regulators of processes central to IBD but also provides the integrated circuits of genetic, molecular, and clinical traits that can be directly queried to interrogate and refine the regulatory framework defining IBD.

Shared genetic variants suggest common pathways in allergy and autoimmune diseases

BACKGROUND

The relationship between allergy and autoimmune disorders is complex and poorly understood.

OBJECTIVE

We sought to investigate commonalities in genetic loci and pathways between allergy and autoimmune diseases to elucidate shared disease mechanisms.

METHODS

We meta-analyzed 2 genome-wide association studies on self-reported allergy and sensitization comprising a total of 62,330 subjects. These results were used to calculate enrichment for single nucleotide polymorphisms (SNPs) previously associated with autoimmune diseases. Furthermore, we probed for enrichment within genetic pathways and of transcription factor binding sites and characterized commonalities in variant burden on tissue-specific regulatory sites by calculating the enrichment of allergy SNPs falling in gene regulatory regions in various cells using Encode Roadmap DNase-hypersensitive site data. Finally, we compared the allergy data with those of all known diseases.

RESULTS

Among 290 loci previously associated with 16 autoimmune diseases, we found a significant enrichment of loci also associated with allergy (P = 1.4e-17) encompassing 29 loci at a false discovery rate of less than 0.05. Such enrichment seemed to be a general characteristic for autoimmune diseases. Among the common loci, 48% had the same direction of effect for allergy and autoimmune diseases. Additionally, we observed an enrichment of allergy SNPs falling within immune pathways and regions of chromatin accessible in immune cells that was also represented in patients with autoimmune diseases but not those with other diseases.

CONCLUSION

We identified shared susceptibility loci and commonalities in pathways between allergy and autoimmune diseases, suggesting shared disease mechanisms. Further studies of these shared genetic mechanisms might help in understanding the complex relationship between these diseases, including the parallel increase in disease prevalence.

rs2841277 (PLD4) is associated with susceptibility and rs4672495 is associated with disease activity in rheumatoid arthritis

Rheumatoid arthritis (RA) is one of the most common autoimmune diseases, can lead to long-term joint damage, chronic pain, and loss of motor function in the hands, and may share some common genetic factors with other autoimmune disorders, such as ankylosing spondylitis (AS). Many single-nucleotide polymorphisms (SNPs) were reported by genome-wide association studies (GWASs) of RA, but some of them have not been examined in the Taiwanese population. In this study, for 15 SNPs reported in previous RA and AS GWASs, we investigated their association with RA in a Taiwanese population. Based on 334 RA patients recruited from the Taichung Veterans General Hospital and 16,036 healthy subjects from the Taiwan Biobank (TWB) project, we observed that subjects having minor allele C at rs2841277 (phospholipase D family, member 4 (PLD4)) have lower susceptibility of RA, compare to those having genotype TT (Odds ratio (OR) = 0.6, p = 3.0 × 10⁻⁶). Among the RA patients, we observed that subjects having GG at rs4672495 have a lower proportion of severe RA, compare to other subjects (OR = 0.09, p = 5.6 × 10⁻³). Results of a bioinformatics approach showed that rs2841277 is able to influence expression of LINC00638 and AHNAK2 and rs4672495 is able to influence the expression of B3GNT2. In summary, this study replicated an association of rs2841277 with RA susceptibility and showed an AS-associated SNP, rs4672495, is associated with RA activity in the Taiwanese population.

Notch4 and mhc class II polymorphisms are associated with hcv-related benign and malignant lymphoproliferative diseases

Mixed cryoglobulinemia (MC), is a HCV-related, clinically benign, lymphoproliferative disorder (LPD) that may evolve into a non Hodgkin's lymphoma (NHL). Significant associations were found between two single nucleotide polymorphisms near NOTCH4 (rs2071286) and the HLA class II (rs9461776) genes and HCV-related MC syndrome (MCS). We analyzed NOTCH4 rs2071286 and HLA-II rs9461776 in 3 HCV-related LPD groups (asymptomatic MC, MCS, NHL) with HCV infection without lymphoproliferative disorders.

We found a positive relationship between NOTCH4 rs207186 T minor allele frequency (MAF) and patients with HCV-related LPDs at risk of NHL (Chi-square test for trend = 14.84 p = 0.0001), in accordance with an over-dominant model in the NHL group (CT vs CC + TT, OR=1.88, 95% CI 1.24–2.83, p = 0.0026).

Regarding HLA II rs9461776, G MAF increased in patients with HCV-related LPDs at risk of NHL (Chi-square test for trend = 8.40 p = 0.0038), in accordance with a recessive genotypic model in the NHL group (G/G vs A/A + A/G, OR = 11.07, 95% CI 2.37–51.64, p = 0.0022).

Both NOTCH4 rs2071286 and HLA-II rs9461776 were present on chromosome 6 and showed D’ and r values of linkage disequilibrium (LD) of about 0.5 values, thereby suggesting there is no extensive LD in the HCV+ population.

This data shows that the previously demonstrated association between NOTCH4 rs2071286 and HLA-II rs9461776 polymorphisms and HCV-related MCS could be extended to overall patients with HCV-related LPDs. The significant relationship between rs2071286 and rs9461776 MAF and the increased risk for NHL, suggests their use as non-invasive markers to categorize patients at risk of lymphoma.

Generating testable hypotheses for schizophrenia and rheumatoid arthritis pathogenesis by integrating epidemiological, genomic, and protein interaction data

Patients with schizophrenia and their relatives have reduced prevalence of rheumatoid arthritis. Schizophrenia and rheumatoid arthritis genome-wide association studies also indicate negative genetic correlations, suggesting that there may be shared pathogenesis at the DNA level or downstream. A portion of the inverse prevalence could be attributed to pleiotropy, i.e., variants of a single nucleotide polymorphism that could confer differential risk for these disorders. To study the basis for such an interrelationship, we initially compared lists of single nucleotide polymorphisms with significant genetic associations (p < 1e-8) for schizophrenia or rheumatoid arthritis, evaluating patterns of linkage disequilibrium and apparent pleiotropic risk profiles. Single nucleotide polymorphisms that conferred risk for both schizophrenia and rheumatoid arthritis were localized solely to the extended HLA region. Among single nucleotide polymorphisms that conferred differential risk for schizophrenia and rheumatoid arthritis, the majority were localized to HLA-B, TNXB, NOTCH4, HLA-C, HCP5, MICB, PSORS1C1, and C6orf10; published functional data indicate that HLA-B and HLA-C have the most plausible pathogenic roles in both disorders. Interactomes of these eight genes were constructed from protein-protein interaction information using publicly available databases and novel computational predictions. The genes harboring apparently pleiotropic single nucleotide polymorphisms are closely connected to rheumatoid arthritis and schizophrenia associated genes through common interacting partners. A separate and independent analysis of the interactomes of rheumatoid arthritis and schizophrenia genes showed a significant overlap between the two interactomes and that they share several common pathways, motivating functional studies suggesting a relationship in the pathogenesis of schizophrenia/rheumatoid arthritis.

[Comorbid autoimmune pathology in patients treated with disease modifying drugs]

Because of intensive growth of the prevalence of multiple sclerosis (MS) and other autoimmune diseases (AID) during the last years, the comorbidity of MS and AID is not a rarity. In this literature review, the development of comorbid AID in patients with MS is considered to be the probable complication of disease modifying therapy with drugs of different groups. The authors present the own data on the prevalence of comorbid autoimmune pathology in patients with MS treated with disease modifying drugs.

rs657075 (CSF2) Is Associated with the Disease Phenotype (BAS-G) of Ankylosing Spondylitis

Ankylosing spondylitis (AS) is a systemic autoimmune disease mainly affecting the lumbar spine and sacroiliac joints, and exhibits peripheral inflammatory arthropathy. More than 25 loci have been identified as associated with AS. Because both AS and rheumatoid arthritis (RA) are autoimmune diseases that may share some common genetic factors, we therefore examined if the newly identified RA genetic polymorphisms were associated with AS in a Taiwanese population. In this study, we enrolled 475 AS patients and 11,301 healthy subjects from a Taiwanese biobank as controls. Although none of single-nucleotide polymorphisms (SNPs) were associated with the susceptibility to AS, the AS disease index Bath AS Global (BAS-G) clinical phenotype was observed as significantly correlated to the AA genotype of rs657075 (CSF2). The significance remains after gender/age/disease duration adjustment and after group categorization by human leukocyte antigen-B 27 (HLA-B27) genotype. We further investigated the possible functions of rs657075 through bioinformatics approaches. Results revealed that polymorphism of rs657075 is able to influence the expression of acyl-CoA synthetase long-chain family member 6 (ACSL6). In conclusion, our study indicated that rs657075 (CSF2) is strongly associated with the AS disease index Bath AS Global (BAS-G) clinical phenotype.

Biomechanisms of Comorbidity: Reviewing Integrative Analyses of Multi-omics Datasets and Electronic Health Records

OBJECTIVES

Disease comorbidity is a pervasive phenomenon impacting patients' health outcomes, disease management, and clinical decisions. This review presents past, current and future research directions leveraging both phenotypic and molecular information to uncover disease similarity underpinning the biology and etiology of disease comorbidity.

METHODS

We retrieved ~130 publications and retained 59, ranging from 2006 to 2015, that comprise a minimum number of five diseases and at least one type of biomolecule. We surveyed their methods, disease similarity metrics, and calculation of comorbidities in the electronic health records, if present.

RESULTS

Among the surveyed studies, 44% generated or validated disease similarity metrics in context of comorbidity, with 60% being published in the last two years. As inputs, 87% of studies utilized intragenic loci and proteins while 13% employed RNA (mRNA, LncRNA or miRNA). Network modeling was predominantly used (35%) followed by statistics (28%) to impute similarity between these biomolecules and diseases. Studies with large numbers of biomolecules and diseases used network models or naïve overlap of disease-molecule associations, while machine learning, statistics, and information retrieval were utilized in smaller and moderate sized studies. Multiscale computations comprising shared function, network topology, and phenotypes were performed exclusively on proteins.

CONCLUSION

This review highlighted the growing methods for identifying the molecular mechanisms underpinning comorbidities that leverage multiscale molecular information and patterns from electronic health records. The survey unveiled that intergenic polymorphisms have been overlooked for similarity imputation compared to their intragenic counterparts, offering new opportunities to bridge the mechanistic and similarity gaps of comorbidity.

Integrative analysis for identification of shared markers from various functional cells/tissues for rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease. So far, it is unclear whether there exist common RA-related genes shared in different tissues/cells. In this study, we conducted an integrative analysis on multiple datasets to identify potential shared genes that are significant in multiple tissues/cells for RA. Seven microarray gene expression datasets representing various RA-related tissues/cells were downloaded from the Gene Expression Omnibus (GEO). Statistical analyses, testing both marginal and joint effects, were conducted to identify significant genes shared in various samples. Followed-up analyses were conducted on functional annotation clustering analysis, protein-protein interaction (PPI) analysis, gene-based association analysis, and ELISA validation analysis in in-house samples. We identified 18 shared significant genes, which were mainly involved in the immune response and chemokine signaling pathway. Among the 18 genes, eight genes (PPBP, PF4, HLA-F, S100A8, RNASEH2A, P2RY6, JAG2, and PCBP1) interact with known RA genes. Two genes (HLA-F and PCBP1) are significant in gene-based association analysis (P = 1.03E-31, P = 1.30E-2, respectively). Additionally, PCBP1 also showed differential protein expression levels in in-house case-control plasma samples (P = 2.60E-2). This study represented the first effort to identify shared RA markers from different functional cells or tissues. The results suggested that one of the shared genes, i.e., PCBP1, is a promising biomarker for RA.

Urine metabolome profiling of immune-mediated inflammatory diseases

BACKGROUND

Immune-mediated inflammatory diseases (IMIDs) are a group of complex and prevalent diseases where disease diagnostic and activity monitoring is highly challenging. The determination of the metabolite profiles of biological samples is becoming a powerful approach to identify new biomarkers of clinical utility. In order to identify new metabolite biomarkers of diagnosis and disease activity, we have performed the first large-scale profiling of the urine metabolome of the six most prevalent IMIDs: rheumatoid arthritis, psoriatic arthritis, psoriasis, systemic lupus erythematosus, Crohn's disease, and ulcerative colitis.

METHODS

Using nuclear magnetic resonance, we analyzed the urine metabolome in a discovery cohort of 1210 patients and 100 controls. Within each IMID, two patient subgroups were recruited representing extreme disease activity (very high vs. very low). Metabolite association analysis with disease diagnosis and disease activity was performed using multivariate linear regression in order to control for the effects of clinical, epidemiological, or technical variability. After multiple test correction, the most significant metabolite biomarkers were validated in an independent cohort of 1200 patients and 200 controls.

RESULTS

In the discovery cohort, we identified 28 significant associations between urine metabolite levels and disease diagnosis and three significant metabolite associations with disease activity (P FDR < 0.05). Using the validation cohort, we validated 26 of the diagnostic associations and all three metabolite associations with disease activity (P FDR < 0.05). Combining all diagnostic biomarkers using multivariate classifiers we obtained a good disease prediction accuracy in all IMIDs and particularly high in inflammatory bowel diseases. Several of the associated metabolites were found to be commonly altered in multiple IMIDs, some of which can be considered as hub biomarkers. The analysis of the metabolic reactions connecting the IMID-associated metabolites showed an over-representation of citric acid cycle, phenylalanine, and glycine-serine metabolism pathways.

CONCLUSIONS

This study shows that urine is a source of biomarkers of clinical utility in IMIDs. We have found that IMIDs show similar metabolic changes, particularly between clinically similar diseases and we have found, for the first time, the presence of hub metabolites. These findings represent an important step in the development of more efficient and less invasive diagnostic and disease monitoring methods in IMIDs.

Reduction of GPSM3 expression akin to the arthritis-protective SNP rs204989 differentially affects migration in a neutrophil model

G Protein Signaling Modulator-3 (GPSM3) is a leukocyte-specific regulator of G protein-coupled receptors (GPCRs), which binds inactivated Gα_i·GDP subunits and precludes their reassociation with Gβγ subunits. GPSM3 deficiency protects mice from inflammatory arthritis and, in humans, GPSM3 single nucleotide polymorphisms (SNPs) are inversely associated with the risk of rheumatoid arthritis development; recently, these polymorphisms were linked to one particular SNP (rs204989) that decreases GPSM3 transcript abundance. However, the precise role of GPSM3 in leukocyte biology is unknown. Here we show that GPSM3 is induced in the human promyelocytic leukemia NB4 cell line following retinoic acid treatment, which differentiates this cell line into a model of neutrophil physiology (NB4*). Reducing GPSM3 expression in NB4* cells, akin to the effect ascribed to the rs204989 C>T transition, disrupts cellular migration toward leukotriene B4 (LTB4) and (to a lesser extent) interleukin-8 (a.k.a. IL-8 or CXCL8), but not migration toward formylated peptides (fMLP). As the chemoattractants LTB4 and CXCL8 are involved in recruitment of neutrophils to the arthritic joint, our results suggest that the arthritis-protective GPSM3 SNP rs204989 may act to decrease neutrophil chemoattractant responsiveness.

Missing heritability of complex diseases: Enlightenment by genetic variants from intermediate phenotypes

Diseases of complex origin have a component of quantitative genetics that contributes to their susceptibility and phenotypic variability. However, after several studies, a major part of the genetic component of complex phenotypes has still not been found, a situation known as "missing heritability." Although there have been many hypotheses put forward to explain the reasons for the missing heritability, its definitive causes remain unknown. Complex diseases are caused by multiple intermediate phenotypes involved in their pathogenesis and, very often, each one of these intermediate phenotypes also has a component of quantitative inheritance. Here we propose that at least part of the missing heritability can be explained by the genetic component of intermediate phenotypes that is not detectable at the level of the main complex trait. At the same time, the identification of the genetic component of intermediate phenotypes provides an opportunity to identify part of the missing heritability of complex diseases.

Constraints on Biological Mechanism from Disease Comorbidity Using Electronic Medical Records and Database of Genetic Variants

Patterns of disease co-occurrence that deviate from statistical independence may represent important constraints on biological mechanism, which sometimes can be explained by shared genetics. In this work we study the relationship between disease co-occurrence and commonly shared genetic architecture of disease. Records of pairs of diseases were combined from two different electronic medical systems (Columbia, Stanford), and compared to a large database of published disease-associated genetic variants (VARIMED); data on 35 disorders were available across all three sources, which include medical records for over 1.2 million patients and variants from over 17,000 publications. Based on the sources in which they appeared, disease pairs were categorized as having predominant clinical, genetic, or both kinds of manifestations. Confounding effects of age on disease incidence were controlled for by only comparing diseases when they fall in the same cluster of similarly shaped incidence patterns. We find that disease pairs that are overrepresented in both electronic medical record systems and in VARIMED come from two main disease classes, autoimmune and neuropsychiatric. We furthermore identify specific genes that are shared within these disease groups.