Rare, low-frequency, and common variants in the protein-coding sequence of biological candidate genes from GWASs contribute to risk of rheumatoid arthritis

Large-scale DNA sequencing identifies rare variants associated with Systemic Lupus Erythematosus susceptibility in known risk genes

The identification of rare genetic variants associated to Systemic Lupus Erythematosus (SLE) could also help to understand the pathogenic mechanisms at the basis of the disease. In this study we have analyzed a cohort of 200 Italian SLE patients in order to explore the rare protein-coding variants in five genes (TNFAIP3, STAT4, IL10, TRAF3IP2, and HCP5) already investigated for commons variants found associated in our previous studies. Genomic DNA of 200 SLE patients was sequenced by whole exome sequencing. The identified variants were filtered by frequency and evaluated by in silico predictions. Allelic association analysis was performed with standard Fisher's exact test. Introducing a cutoff at MAF < 0.01, a total of 19 rare variants were identified. Seven of these variants were ultra-rare (MAF < 0.001) and six were absent in the GnomAD database. For TNFAIP3 gene, the variant c.A1939C was observed in 4 SLE patients and it is located in a region enriched in phosphorylation sites and affects the predict affinity of specific kinases. In TRAF3IP2 gene, we observed 5 different rare variants, including the novel variant c.G410A, located in the region that mediates interaction with TRAF6, and therefore a possible risk factor for SLE development. In STAT4 gene, we identified 6 different rare variants. Among these, three missense variants decrease the stability of this protein. Moreover, 3 novel rare variants were detected in 3 SLE patients. In particular, c.A767T variant was predicted as damaging by six prediction tools. Concluding, we have observed that even in genes whose common variability is associated with SLE susceptibility, it is possible to identify rare variants that could have a strong effect in the disease development and could therefore allow a better understanding of the functional domain involved.

MYLK*FLNB and DOCK1*LAMA2 gene-gene interactions associated with rheumatoid arthritis in the focal adhesion pathway

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease caused by a combination of genetic and environmental factors. Rare variants with low predicted effects in genes participating in the same biological function might be involved in developing complex diseases such as RA. From whole-exome sequencing (WES) data, we identified genes containing rare non-neutral variants with complete penetrance and no phenocopy in at least one of nine French multiplex families. Further enrichment analysis highlighted focal adhesion as the most significant pathway. We then tested if interactions between the genes participating in this function would increase or decrease the risk of developing RA disease. The model-based multifactor dimensionality reduction (MB-MDR) approach was used to detect epistasis in a discovery sample (19 RA cases and 11 healthy individuals from 9 families and 98 unrelated CEU controls from the International Genome Sample Resource). We identified 9 significant interactions involving 11 genes (MYLK, FLNB, DOCK1, LAMA2, RELN, PIP5K1C, TNC, PRKCA, VEGFB, ITGB5, and FLT1). One interaction (MYLK*FLNB) increasing RA risk and one interaction decreasing RA risk (DOCK1*LAMA2) were confirmed in a replication sample (200 unrelated RA cases and 91 GBR unrelated controls). Functional and genomic data in RA samples or relevant cell types argue the key role of these genes in RA.

Low-frequency and rare genetic variants associated with rheumatoid arthritis risk

Rheumatoid arthritis (RA) has an estimated heritability of nearly 50%, which is particularly high in seropositive RA. HLA alleles account for a large proportion of this heritability, in addition to many common single-nucleotide polymorphisms with smaller individual effects. Low-frequency and rare variants, such as those captured by next-generation sequencing, can also have a large role in heritability in some individuals. Rare variant discovery has informed the development of drugs such as inhibitors of PCSK9 and Janus kinases. Some 34 low-frequency and rare variants are currently associated with RA risk. One variant (19:10352442G>C in TYK2) was identified in five separate studies, and might therefore represent a promising therapeutic target. Following a set of best practices in future studies, including studying diverse populations, using large sample sizes, validating RA and serostatus, replicating findings, adjusting for other variants and performing functional assessment, could help to ensure the relevance of identified variants. Exciting opportunities are now on the horizon for genetics in RA, including larger datasets and consortia, whole-genome sequencing and direct applications of findings in the management, and especially treatment, of RA.

Genome-wide polygenic risk score for rheumatoid arthritis prediction in postmenopausal women

BACKGROUND

Rheumatoid arthritis (RA), a common autoimmune disease, exhibits a vital genetic component. Polygenic risk scores (PRS) derived from genome-wide association studies (GWAS) offer potential utility in predicting disease susceptibility. The present study aimed to develop and validate a PRS for predicting RA risk in postmenopausal women.

METHODS

The study developed a novel PRS using 225,000 genetic variants from a GWAS dataset. The PRS was developed in a cohort of 8967 postmenopausal women and validated in an independent cohort of 6269 postmenopausal women. Among the development cohort, approximately 70% were Hispanic and approximately 30% were African American. The testing cohort comprised approximately 50% Hispanic and 50% Caucasian individuals. Stratification according to PRS quintiles revealed a pronounced gradient in RA prevalence and odds ratios.

RESULTS

High PRS was significantly associated with increased RA risk in individuals aged 60-70 years, ≥ 70 years, and overweight and obese participants. Furthermore, at age 65 years, individuals in the bottom 5% of the PRS distribution have an absolute risk of RA at 30.6% (95% confidence interval = 18.5%-42.6%). The risk increased to 53.8% (95% confidence interval = 42.8%-64.9%) for those in the top 5% of the PRS distribution.

CONCLUSIONS

The PRS developed in the present study is significantly associated with RA risk, showing the potential for early screening of RA in postmenopausal women. This work demonstrates the feasibility of personalized medicine in identifying high-risk individuals for RA, indicating the need for further studies to test the utility of PRS in other populations.

Single Nucleotide Polymorphisms Associated with Rheumatoid Arthritis in Saudi Patients

Rheumatoid arthritis (RA) is a complex, multifactorial disorder with an autoimmune etiology. RA is highly heritable and is associated with both human leucocyte antigen (HLA) and non-HLA genes. We investigated the associations of 33 single nucleotide polymorphisms (SNPs) with RA in the Saudi population.

METHODS

This study included 105 patients with RA and an equal number of age- and sex-matched controls. The patients with RA attended outpatient clinics at King Khalid University Hospital in Riyadh, Saudi Arabia. Blood samples were collected, and DNA was extracted using Qiagen kits. Primers were designed for the 33 selected SNPs using the MassEXTEND primers program, and samples were genotyped on the Sequenom MassARRAY iPLEX platform. The allele frequencies and genotypes were determined for each SNP, and the results obtained for the patients were compared to those for the controls.

RESULTS

The allele and genotype frequencies of six SNPs were significantly associated with RA: rs1188934, rs10919563, rs3087243, rs1980422, rs10499194, and rs629326. The minor alleles of rs1188934, rs10919563, rs10499194, and rs629326 were protective, with odds ratios of 0.542, 0.597, 0.589, and 0.625, and p-values of 0.002, 0.023, 0.013 and 0.036, respectively. In addition, the heterozygote frequencies of two SNPs (rs6859219 and rs11586238) were significantly higher in the controls than in the patients.

CONCLUSIONS

There is considerable heterogeneity in the genetics of RA in different populations, and the SNPs that are associated with RA in some populations are not in others. We studied 33 SNPs and only eight were associated with RA. The remaining SNPs showed no allelic or genotypic associations with RA.

Genome-wide identification of RNA modification-related single nucleotide polymorphisms associated with rheumatoid arthritis

BACKGROUND

RNA modification plays important roles in many biological processes, such as gene expression control. The aim of this study was to identify single nucleotide polymorphisms related to RNA modification (RNAm-SNPs) for rheumatoid arthritis (RA) as putative functional variants.

METHODS

We examined the association of RNAm-SNPs with RA in summary data from a genome-wide association study of 19,234 RA cases and 61,565 controls. We performed eQTL and pQTL analyses for the RNAm-SNPs to find associated gene expression and protein levels. Furthermore, we examined the associations of gene expression and circulating protein levels with RA using two-sample Mendelian randomization analysis methods.

RESULTS

A total of 160 RNAm-SNPs related to m⁶A, m¹A, A-to-I, m⁷G, m⁵C, m⁵U and m⁶Am modifications were identified to be significantly associated with RA. These RNAm-SNPs were located in 62 protein-coding genes, which were significantly enriched in immune-related pathways. RNAm-SNPs in important RA susceptibility genes, such as PADI2, SPRED2, PLCL2, HLA-A, HLA-B, HLA-DRB1, HLA-DPB1, TRAF1 and TXNDC11, were identified. Most of these RNAm-SNPs showed eQTL effects, and the expression levels of 26 of the modifiable genes (e.g., PADI2, TRAF1, HLA-A, HLA-DRB1, HLA-DPB1 and HLA-B) in blood cells were associated with RA. Circulating protein levels, such as CFB, GZMA, HLA-DQA2, IL21, LRPAP1 and TFF3, were affected by RNAm-SNPs and were associated with RA.

CONCLUSION

The present study identified RNAm-SNPs in the reported RA susceptibility genes and suggested that RNAm-SNPs may affect RA risk by affecting the expression levels of corresponding genes and proteins.

Translational impact of omics studies in alopecia areata: recent advances and future perspectives

INTRODUCTION

Alopecia areata (AA) is a non-scarring, hair loss disorder and a common autoimmune-mediated disease with an estimated lifetime risk of about 2%. To date, the treatment of AA is mainly based on suppression or stimulation of the immune response. Genomics and transcriptomics studies generated important insights into the underlying pathophysiology, enabled discovery of molecular disease signatures, which were used in some of the recent clinical trials to monitor drug response and substantiated the consideration of new therapeutic modalities for the treatment of AA such as abatacept, dupilumab, ustekinumab and Janus Kinase (JAK) inhibitors.

AREAS COVERED

In this review, genomics and transcriptomics studies in AA are discussed in detail with particular emphasis on their past and prospective translational impacts. Microbiome studies are also briefly introduced.

EXPERT OPINION

The generation of large datasets using the new high-throughput technologies has revolutionized medical research and AA has also benefited from the wave of omics studies. However, the limitations associated with JAK inhibitors and clinical heterogeneity in AA patients underscore the necessity for continuing omics research in AA for discovery of novel therapeutic modalities and development of clinical tools for precision medicine.

Bench Research Informed by GWAS Results

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.

Advancing drug discovery using the power of the human genome

Human genetics plays an increasingly important role in drug development and population health. Here we review the history of human genetics in the context of accelerating the discovery of therapies, present examples of how human genetics evidence supports successful drug targets, and discuss how polygenic risk scores could be beneficial in various clinical settings. We highlight the value of direct-to-consumer platforms in the era of fast-paced big data biotechnology, and how diverse genetic and health data can benefit society. © 2021 23andMe, Inc. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Whole mitochondrial genome analysis in Chinese patients with keratoconus

Purpose

Keratoconus (KC) is a corneal disorder characterized by corneal ectasia, progressive corneal thinning, and conical protrusion. This study aimed to elucidate the mitochondrial gene profile in Chinese patients with KC, analyze the mitochondrial haplogroup and heteroplasmy, and further explore the association between mitochondrial genes and KC.

Methods

Mitochondrial sequencing was conducted on 100 patients with KC and 100 matched controls. Haplogroup analysis was conducted with logistic regression analysis. The heteroplasmy was analyzed with ANOVA (ANOVA) and Student t test. Sequence kernel association tests (SKATs) were performed to analyze the association between mitochondrial genes and KC. Mtoolbox, Mitoclass.1, and APOGEE were used to estimate the impact of the identified variants in protein-coding genes. PON-mt-tRNA was used to annotate the impact of the variants in tRNA. RNAstructure was used to predict the secondary structures of native and mutated tRNAs.

Results

We identified 689 variants in patients with KC and 725 variants in controls (with 308 variants shared by both). The mitochondrial haplogroups exhibited no statistically significant differences between the two groups. Based on the heteroplasmy analysis, the number of heteroplasmic variants in the complete mitochondrial genome, RNA coding regions, and noncoding regions were statistically significantly different in the KC cases and controls (p<0.05). The heteroplasmic levels of the m.16180_16182delAA, m.16182insC, and m.14569 G>C variants in the KC cases were statistically significantly higher than those in the controls (p<0.05). The SKAT analysis showed that the COX3 and TRNH genes were statistically significantly associated with KC (p<0.05). Among the nine variants of COX3 included in the SKAT analysis (m.9300G>A, m.9316T>C, m.9327A>G, m.9355A>G, m.9468A>G, m.9612G>A, m.9804G>A, m.9957G>A, and m.9966 G>A), m.9612G>A was predicted to be deleterious by Mtoolbox. The m.9316T>C, m.9327A>G, m.9355A>G, m.9612G>A, m.9804G>A, and m.9957G>A variants were predicted to be damaging by Mitoclass.1. The m.9355A>G and m.9804G>A variants were predicted to be pathogenic by APOGEE. All identified variants located in TRNH (m.12153C>T, m.12178C>T, and m.12192G>A) were predicted to be neutral by the PON-mt-tRNA website.

Conclusions

This study presents the mitochondrial gene profile of Chinese patients with KC and demonstrated that the COX3 and TRNH genes were associated with KC.

Emerging roles of rare and low-frequency genetic variants in type 1 diabetes mellitus

Type 1 diabetes mellitus (T1DM) is defined as an autoimmune disorder and has enormous complexity and heterogeneity. Although its precise pathogenic mechanisms are obscure, this disease is widely acknowledged to be precipitated by environmental factors in individuals with genetic susceptibility. To date, the known susceptibility loci, which have mostly been identified by genome-wide association studies, can explain 80%–85% of the heritability of T1DM. Researchers believe that at least a part of its missing genetic component is caused by undetected rare and low-frequency variants. Most common variants have only small to modest effect sizes, which increases the difficulty of dissecting their functions and restricts their potential clinical application. Intriguingly, many studies have indicated that rare and low-frequency variants have larger effect sizes and play more significant roles in susceptibility to common diseases, including T1DM, than common variants do. Therefore, better recognition of rare and low-frequency variants is beneficial for revealing the genetic architecture of T1DM and for providing new and potent therapeutic targets for this disease. Here, we will discuss existing challenges as well as the great significance of this field and review current knowledge of the contributions of rare and low-frequency variants to T1DM.

Unique roles of rare variants in the genetics of complex diseases in humans

Genome-wide association studies have identified >10,000 genetic variants associated with various phenotypes and diseases. Although the majority are common variants, rare variants with >0.1% of minor allele frequency have been investigated by imputation and using disease-specific custom SNP arrays. Rare variants sequencing analysis mainly revealed have played unique roles in the genetics of complex diseases in humans due to their distinctive features, in contrast to common variants. Unique roles are hypothesis-free evidence for gene causality, a precise target of functional analysis for understanding disease mechanisms, a new favorable target for drug development, and a genetic marker with high disease risk for personalized medicine. As whole-genome sequencing continues to identify more rare variants, the roles associated with rare variants will also increase. However, a better estimation of the functional impact of rare variants across whole genome is needed to enhance their contribution to improvements in human health.

Impact of ICD10 and secular changes on electronic medical record rheumatoid arthritis algorithms

OBJECTIVE

The objective of this study was to compare the performance of an RA algorithm developed and trained in 2010 utilizing natural language processing and machine learning, using updated data containing ICD10, new RA treatments, and a new electronic medical records (EMR) system.

METHODS

We extracted data from subjects with ≥1 RA International Classification of Diseases (ICD) codes from the EMR of two large academic centres to create a data mart. Gold standard RA cases were identified from reviewing a random 200 subjects from the data mart, and a random 100 subjects who only have RA ICD10 codes. We compared the performance of the following algorithms using the original 2010 data with updated data: (i) a published 2010 RA algorithm; (ii) updated algorithm, incorporating ICD10 RA codes and new DMARDs; and (iii) published algorithm using ICD codes only, ICD RA code ≥3.

RESULTS

The gold standard RA cases had mean age 65.5 years, 78.7% female, 74.1% RF or antibodies to cyclic citrullinated peptide (anti-CCP) positive. The positive predictive value (PPV) for ≥3 RA ICD was 54%, compared with 56% in 2010. At a specificity of 95%, the PPV of the 2010 algorithm and the updated version were both 91%, compared with 94% (95% CI: 91, 96%) in 2010. In subjects with ICD10 data only, the PPV for the updated 2010 RA algorithm was 93%.

CONCLUSION

The 2010 RA algorithm validated with the updated data with similar performance characteristics as the 2010 data. While the 2010 algorithm continued to perform better than the rule-based approach, the PPV of the latter also remained stable over time.

Latin American Genes: The Great Forgotten in Rheumatoid Arthritis

The successful implementation of personalized medicine will rely on the integration of information obtained at the level of populations with the specific biological, genetic, and clinical characteristics of an individual. However, because genome-wide association studies tend to focus on populations of European descent, there is a wide gap to bridge between Caucasian and non-Caucasian populations before personalized medicine can be fully implemented, and rheumatoid arthritis (RA) is not an exception. In this review, we discuss advances in our understanding of genetic determinants of RA risk among global populations, with a focus on the Latin American population. Geographically restricted genetic diversity may have important implications for health and disease that will remain unknown until genetic association studies have been extended to include Latin American and other currently under-represented ancestries. The next few years will witness many breakthroughs in personalized medicine, including applications for common diseases and risk stratification instruments for targeted prevention/intervention strategies. Not all of these applications may be extrapolated from the Caucasian experience to Latin American or other under-represented populations.

Power and Sample Size Calculations for Genetic Association Studies in the Presence of Genetic Model Misspecification

INTRODUCTION

When analyzing data from large-scale genetic association studies, such as targeted or genome-wide resequencing studies, it is common to assume a single genetic model, such as dominant or additive, for all tests of association between a given genetic variant and the phenotype. However, for many variants, the chosen model will result in poor model fit and may lack statistical power due to model misspecification.

OBJECTIVE

We develop power and sample size calculations for tests of gene and gene × environment interaction, allowing for misspecification of the true mode of genetic susceptibility.

METHODS

The power calculations are based on a likelihood ratio test framework and are implemented in an open-source R package ("genpwr").

RESULTS

We use these methods to develop an analysis plan for a resequencing study in idiopathic pulmonary fibrosis and show that using a 2-degree of freedom test can increase power to detect recessive genetic effects while maintaining power to detect dominant and additive effects.

CONCLUSIONS

Understanding the impact of model misspecification can aid in study design and developing analysis plans that maximize power to detect a range of true underlying genetic effects. In particular, these calculations help identify when a multiple degree of freedom test or other robust test of association may be advantageous.

Rare genetic variants in systemic autoimmunity

Autoimmune disease is a substantial cause of morbidity and is strongly influenced by genetic risk. Extensive efforts have characterized the overall genetic basis of many autoimmune diseases, typically by investigation of common variants. While these common variants have modest effects and may cumulatively predispose to disease, it is also increasingly apparent that rare variants have significantly greater effect on phenotype and are likely to contribute to autoimmune disease. Recent advances have illustrated the next fundamental step in elucidating the genetic basis of autoimmunity, moving beyond association to demonstrate the functional consequences of these variants.

HLA associations in inflammatory arthritis: emerging mechanisms and clinical implications

Our understanding of the mechanisms underlying HLA associations with inflammatory arthritis continues to evolve. Disease associations have been refined, and interactions of HLA genotype with other genes and environmental risk factors in determining disease risk have been identified. This Review provides basic information on the genetics and molecular function of HLA molecules, as well as general features of HLA associations with disease. Evidence is discussed regarding the various peptide-dependent and peptide-independent mechanisms by which HLA alleles might contribute to the pathogenesis of three types of inflammatory arthritis: rheumatoid arthritis, spondyloarthritis and systemic juvenile idiopathic arthritis. Also discussed are HLA allelic associations that shed light on the genetic heterogeneity of inflammatory arthritides and on the relationships between adult and paediatric forms of arthritis. Clinical implications range from improved diagnosis and outcome prediction to the possibility of using HLA associations in developing personalized strategies for the treatment and prevention of these diseases.

The Potential Role of Genomic Medicine in the Therapeutic Management of Rheumatoid Arthritis

During the last decade, important advances have occurred regarding understanding of the pathogenesis and treatment of rheumatoid arthritis (RA). Nevertheless, response to treatment is not universal, and choosing among different therapies is currently based on a trial and error approach. The specific patient’s genetic background influences the response to therapy for many drugs: In this sense, genomic studies on RA have produced promising insights that could help us find an effective therapy for each patient. On the other hand, despite the great knowledge generated regarding the genetics of RA, most of the investigations performed to date have focused on identifying common variants associated with RA, which cannot explain the complete heritability of the disease. In this regard, rare variants could also contribute to this missing heritability as well as act as biomarkers that help in choosing the right therapy. In the present article, different aspects of genetics in the pathogenesis and treatment of RA are reviewed, from large-scale genomic studies to specific rare variant analyses. We also discuss the shared genetic architecture existing among autoimmune diseases and its implications for RA therapy, such as drug repositioning.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A novel nonsense variant in SUPT20H gene associated with Rheumatoid Arthritis identified by Whole Exome Sequencing of multiplex families

The triggering and development of Rheumatoid Arthritis (RA) is conditioned by environmental and genetic factors. Despite the identification of more than one hundred genetic variants associated with the disease, not all the cases can be explained. Here, we performed Whole Exome Sequencing in 9 multiplex families (N = 30) to identify rare variants susceptible to play a role in the disease pathogenesis. We pre-selected 77 genes which carried rare variants with a complete segregation with RA in the studied families. Follow-up linkage and association analyses with pVAAST highlighted significant RA association of 43 genes (p-value < 0.05 after 106 permutations) and pinpointed their most likely causal variant. We re-sequenced the 10 most significant likely causal variants (p-value ≤ 3.78*10-3 after 106 permutations) in the extended pedigrees and 9 additional multiplex families (N = 110). Only one SNV in SUPT20H: c.73A>T (p.Lys25*), presented a complete segregation with RA in an extended pedigree with early-onset cases. In summary, we identified in this study a new variant associated with RA in SUPT20H gene. This gene belongs to several biological pathways like macro-autophagy and monocyte/macrophage differentiation, which contribute to RA pathogenesis. In addition, these results showed that analyzing rare variants using a family-based approach is a strategy that allows to identify RA risk loci, even with a small dataset.

Gene editing in the context of an increasingly complex genome

The reporting of the first draft of the human genome in 2000 brought with it much hope for the future in what was felt as a paradigm shift toward improved health outcomes. Indeed, we have now mapped the majority of variation across human populations with landmark projects such as 1000 Genomes; in cancer, we have catalogued mutations across the primary carcinomas; whilst, for other diseases, we have identified the genetic variants with strongest association. Despite this, we are still awaiting the genetic revolution in healthcare to materialise and translate itself into the health benefits for which we had hoped. A major problem we face relates to our underestimation of the complexity of the genome, and that of biological mechanisms, generally. Fixation on DNA sequence alone and a 'rigid' mode of thinking about the genome has meant that the folding and structure of the DNA molecule -and how these relate to regulation- have been underappreciated. Projects like ENCODE have additionally taught us that regulation at the level of RNA is just as important as that at the spatiotemporal level of chromatin.In this review, we chart the course of the major advances in the biomedical sciences in the era pre- and post the release of the first draft sequence of the human genome, taking a focus on technology and how its development has influenced these. We additionally focus on gene editing via CRISPR/Cas9 as a key technique, in particular its use in the context of complex biological mechanisms. Our aim is to shift the mode of thinking about the genome to that which encompasses a greater appreciation of the folding of the DNA molecule, DNA- RNA/protein interactions, and how these regulate expression and elaborate disease mechanisms.Through the composition of our work, we recognise that technological improvement is conducive to a greater understanding of biological processes and life within the cell. We believe we now have the technology at our disposal that permits a better understanding of disease mechanisms, achievable through integrative data analyses. Finally, only with greater understanding of disease mechanisms can techniques such as gene editing be faithfully conducted.

Effective discovery of rare variants by pooled target capture sequencing: A comparative analysis with individually indexed target capture sequencing

Identification of all genetic variants associated with complex traits is one of the most important goals in modern human genetics. Genome-wide association studies (GWAS) have been successfully applied to identify common variants, which thus far explain only small portion of heritability. Interests in rare variants have been increasingly growing as an answer for this missing heritability. While next-generation sequencing allows detection of rare variants, its cost is still prohibitively high to sequence a large number of human DNA samples required for rare variant association studies. In this study, we evaluated the sensitivity and specificity of sequencing for pooled DNA samples of multiple individuals (Pool-seq) as a cost-effective and robust approach for rare variant discovery. We comparatively analyzed Pool-seq vs. individual-seq of indexed target capture of up to 960 genes in ∼1000 individuals, followed by independent genotyping validation studies. We found that Pool-seq was as effective and accurate as individual-seq in detecting rare variants and accurately estimating their minor allele frequencies (MAFs). Our results suggest that Pool-seq can be used as an efficient and cost-effective method for discovery of rare variants for population-based sequencing studies in individual laboratories.

ACO2 homozygous missense mutation associated with complicated hereditary spastic paraplegia

Objective

To identify the clinical characteristics and genetic etiology of a family affected with hereditary spastic paraplegia (HSP).

Methods

Clinical, genetic, and functional analyses involving genome-wide linkage coupled to whole-exome sequencing in a consanguineous family with complicated HSP.

Results

A homozygous missense mutation was identified in the ACO2 gene (c.1240T>G p.Phe414Val) that segregated with HSP complicated by intellectual disability and microcephaly. Lymphoblastoid cell lines of homozygous carrier patients revealed significantly decreased activity of the mitochondrial aconitase enzyme and defective mitochondrial respiration. ACO2 encodes mitochondrial aconitase, an essential enzyme in the Krebs cycle. Recessive mutations in this gene have been previously associated with cerebellar ataxia.

Conclusions

Our findings nominate ACO2 as a disease-causing gene for autosomal recessive complicated HSP and provide further support for the central role of mitochondrial defects in the pathogenesis of HSP.

Investigating multiple dysregulated pathways in rheumatoid arthritis based on pathway interaction network

The traditional methods of identifying biomarkers in rheumatoid arthritis (RA) have focussed on the differentially expressed pathways or individual pathways, which however, neglect the interactions between pathways. To better understand the pathogenesis of RA, we aimed to identify dysregulated pathway sets using a pathway interaction network (PIN), which considered interactions among pathways. Firstly, RA-related gene expression profile data, protein-protein interactions (PPI) data and pathway data were taken up from the corresponding databases. Secondly, principal component analysis method was used to calculate the pathway activity of each of the pathway, and then a seed pathway was identified using data gleaned from the pathway activity. A PIN was then constructed based on the gene expression profile, pathway data, and PPI information. Finally, the dysregulated pathways were extracted from the PIN based on the seed pathway using the method of support vector machines and an area under the curve (AUC) index. The PIN comprised of a total of 854 pathways and 1064 pathway interactions. The greatest change in the activity score between RA and control samples was observed in the pathway of epigenetic regulation of gene expression, which was extracted and regarded as the seed pathway. Starting with this seed pathway, one maximum pathway set containing 10 dysregulated pathways was extracted from the PIN, having an AUC of 0.8249, and the result indicated that this pathway set could distinguish RA from the controls. These 10 dysregulated pathways might be potential biomarkers for RA diagnosis and treatment in the future.

Identification of potential genetic causal variants for rheumatoid arthritis by whole-exome sequencing

Rheumatoid arthritis (RA) is a highly prevalent chronic autoimmune disease. However, genetic and environmental factors involved in RA pathogenesis are still remained largely unknown. To identify the genetic causal variants underlying pathogenesis and disease progression of RA patients, we undertook the first comprehensive whole-exome sequencing (WES) study in a total of 124 subjects including 58 RA cases and 66 healthy controls in Han Chinese population. We identified 378 novel genes that were enriched with deleterious variants in RA patients using a gene burden test. The further functional effects of associated genetic genes were classified and assessed, including 21 newly identified genes that were involved in the extracellular matrix (ECM)-receptor interaction, protein digestion and absorption, focal adhesion and glycerophospholipid metabolism pathways relevant to RA pathogenesis. Moreover, six pathogenic variants were investigated and structural analysis predicted their potentially functional alteration by homology modeling. Importantly, five novel and rare homozygous variants (NCR3LG1, RAP1GAP, CHCHD5, HIPK2 and DIAPH2) were identified, which may exhibit more functional impact on RA pathogenesis. Notably, 7 genes involved in the olfactory transduction pathway were enriched and associated with RA disease progression. Therefore, we performed an efficient and powerful technique WES in Chinese RA patients and identified novel, rare and common disease causing genes that alter innate immunity pathways and contribute to the risk of RA. Findings in this study may provide potential diagnostic tools and therapeutic strategies for RA patients.

Effects of Amerindian Genetic Ancestry on Clinical Variables and Therapy in Patients with Rheumatoid Arthritis

OBJECTIVE

To define whether Amerindian genetic ancestry correlates with clinical and therapeutic variables in admixed individuals with rheumatoid arthritis (RA) from Latin America.

METHODS

Patients with RA (n = 1347) and healthy controls (n = 1012) from Argentina, Mexico, Chile, and Peru were included. Samples were genotyped for the Immunochip v1 using the Illumina platform. Clinical data were obtained through interviews or the clinical history.

RESULTS

Percentage of Amerindian ancestry was comparable between cases and controls. Morning stiffness (p < 0.0001, OR 0.05), rheumatoid factor (RF; p < 0.0001, OR 0.22), radiographic changes (p < 0.0001, OR 0.05), and higher number of criteria were associated with lower Amerindian ancestry after Bonferroni correction. Higher Amerindian ancestry correlated only with weight loss (p_Bonferroni < 0.0001, OR 2.85). Increased Amerindian ancestry correlated with higher doses of azathioprine (p < 0.0001, OR 163.6) and sulfasalazine (p < 0.0001, OR 48.6), and inversely with methotrexate (p = 0.001, OR 0.35), leflunomide (p = 0.001, OR 0.16), and nonsteroidal antiinflammatory drugs (p_Bonferroni = 0.001, OR 0.37). Only the presence of RF and weight loss were modified after confounders adjustment.

CONCLUSION

Amerindian ancestry protects against most major clinical criteria of RA, but regarding the association of RF with increased European ancestry, age, sex, and smoking are modifiers. Ancestry also correlates with the therapeutic profiles.

Mechanisms of Pediatric Inflammatory Bowel Disease

Inflammatory bowel disease (IBD), including Crohn disease and ulcerative colitis, is characterized by chronic intestinal inflammation due to a complex interaction of genetic determinants, disruption of mucosal barriers, aberrant inflammatory signals, loss of tolerance, and environmental triggers. Importantly, the incidence of pediatric IBD is rising, particularly in children younger than 10 years. In this review, we discuss the clinical presentation of these patients and highlight environmental exposures that may affect disease risk, particularly among people with a background genetic risk. With regard to both children and adults, we review advancements in understanding the intestinal epithelium, the mucosal immune system, and the resident microbiota, describing how dysfunction at any level can lead to diseases like IBD. We conclude with future directions for applying advances in IBD genetics to better understand pathogenesis and develop therapeutics targeting key pathogenic nodes.

Axon guidance pathways served as common targets for human speech/language evolution and related disorders

Human and several nonhuman species share the rare ability of modifying acoustic and/or syntactic features of sounds produced, i.e. vocal learning, which is the important neurobiological and behavioral substrate of human speech/language. This convergent trait was suggested to be associated with significant genomic convergence and best manifested at the ROBO-SLIT axon guidance pathway. Here we verified the significance of such genomic convergence and assessed its functional relevance to human speech/language using human genetic variation data. In normal human populations, we found the affected amino acid sites were well fixed and accompanied with significantly more associated protein-coding SNPs in the same genes than the rest genes. Diseased individuals with speech/language disorders have significant more low frequency protein coding SNPs but they preferentially occurred outside the affected genes. Such patients' SNPs were enriched in several functional categories including two axon guidance pathways (mediated by netrin and semaphorin) that interact with ROBO-SLITs. Four of the six patients have homozygous missense SNPs on PRAME gene family, one youngest gene family in human lineage, which possibly acts upon retinoic acid receptor signaling, similarly as FOXP2, to modulate axon guidance. Taken together, we suggest the axon guidance pathways (e.g. ROBO-SLIT, PRAME gene family) served as common targets for human speech/language evolution and related disorders.

Rare variants, autoimmune disease, and arthritis

PURPOSE OF REVIEW

We review select studies of newly discovered rare variants in autoimmune diseases with a focus on newly described monogenic disorders, rheumatoid arthritis, and systemic lupus erythematosus.

RECENT FINDINGS

Two new monogenic syndromes of inflammatory arthritis were discovered using whole exome sequencing: the coatomer subunit alpha syndrome because of rare mutations in coatomer subunit alpha and haploinsufficiency of A20 resulting from rare mutations in TNFAIP3. Targeted exon sequencing identified rare variants in IL2RA and IL2RB associated with rheumatoid arthritis. Rare variants in TREX1 and other genes associated with monogenic interferonopathies are also associated with systemic lupus erythematosus.

SUMMARY

Rare genetic variants contribute to the heritability of autoimmunity and provide key insight into both novel and previously implicated immunological pathways that are disrupted in autoimmune diseases.

Genetic architecture differences between pediatric and adult-onset inflammatory bowel diseases in the Polish population

Most inflammatory bowel diseases (IBDs) are classic complex disorders represented by common alleles. Here we aimed to define the genetic architecture of pediatric and adult-onset IBDs for the Polish population. A total of 1495 patients were recruited, including 761 patients with Crohn’s disease (CD; 424 pediatric), 734 patients with ulcerative colitis (UC; 390 pediatric), and 934 healthy controls. Allelotyping employed a pooled-DNA genome-wide association study (GWAS) and was validated by individual genotyping. Whole exome sequencing (WES) was performed on 44 IBD patients diagnosed before 6 years of age, 45 patients diagnosed after 40 years of age, and 18 healthy controls. Altogether, out of 88 selected SNPs, 31 SNPs were replicated for association with IBD. A novel BRD2 (rs1049526) association reached significance of P = 5.2 × 10⁻¹¹ and odds ratio (OR) = 2.43. Twenty SNPs were shared between pediatric and adult patients; 1 and 7 were unique to adult-onset and pediatric-onset IBD, respectively. WES identified numerous rare and potentially deleterious variants in IBD-associated or innate immunity-associated genes. Deleterious alleles in both groups were over-represented among rare variants in affected children. Our GWAS revealed differences in the polygenic architecture of pediatric- and adult-onset IBD. A significant accumulation of rare and deleterious variants in affected children suggests a contribution by yet unexplained genetic components.

A Data Fusion Approach to Enhance Association Study in Epilepsy

Among the scientific challenges posed by complex diseases with a strong genetic component, two stand out. One is unveiling the role of rare and common genetic variants; the other is the design of classification models to improve clinical diagnosis and predictive models for prognosis and personalized therapies. In this paper, we present a data fusion framework merging gene, domain, pathway and protein-protein interaction data related to a next generation sequencing epilepsy gene panel. Our method allows integrating association information from multiple genomic sources and aims at highlighting the set of common and rare variants that are capable to trigger the occurrence of a complex disease. When compared to other approaches, our method shows better performances in classifying patients affected by epilepsy.

Update on the genetic architecture of rheumatoid arthritis

Human genetic studies into rheumatoid arthritis (RA) have uncovered more than 100 genetic loci associated with susceptibility to RA and have refined the RA-association model for HLA variants. The majority of RA-risk variants are highly shared across multiple ancestral populations and are located in noncoding elements that might have allele-specific regulatory effects in relevant tissues. Emerging multi-omics data, high-density genotype data and bioinformatic approaches are enabling researchers to use RA-risk variants to identify functionally relevant cell types and biological pathways that are involved in impaired immune processes and disease phenotypes. This Review summarizes reported RA-risk loci and the latest insights from human genetic studies into RA pathogenesis, including how genetic data has helped to identify currently available drugs that could be repurposed for patients with RA and the role of genetics in guiding the development of new drugs.

Mutation-Induced Functional Alterations of CCR6

The Cys-Cys chemokine receptor 6 (CCR6) is a well-established modulator of inflammation. Although several genetic associations have been identified between CCR6 polymorphisms and immune system disorders (e.g., rheumatoid arthritis and Crohn's disease), the pharmacological effects of naturally occurring missense mutations in this receptor have yet to be characterized. In this study, we initially assessed G protein-mediated signaling and observed that wild-type (WT) CCR6 exhibited ligand-independent activity. In addition, we found that the five most frequent CCR6 missense variants (A89T, A150V, R155W, G345S, and A369V) exhibited decreased basal and/or ligand induced Gαi protein signaling. To complement the study of these loss-of-function variants, we engineered a set of constitutively active CCR6 receptors. Selected mutations enhanced basal G protein-mediated signaling up to 3-fold relative to the WT value. Using a bioluminescence resonance energy transfer assay we investigated the ability of each naturally occurring and engineered CCR6 receptor mutant to recruit β-arrestin. In contrast to G protein-mediated signaling, β-arrestin mobilization was largely unperturbed by the naturally occurring loss-of-function CCR6 variants. Elevated recruitment of β-arrestin was observed in one of the engineered constitutively active mutants (T98P). Our results demonstrate that point mutations in CCR6 can result in either a gain or loss of receptor function. These observations underscore the need to explore how CCR6 natural variants may influence immune cell physiology and human disease.

Recent Advances in Defining the Genetic Basis of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is the most common inflammatory arthritis and exhibits genetic overlap with other autoimmune and inflammatory disorders. Although predominant associations with the HLA-DRB1 locus have been known for decades, recent data have revealed additional insight into the likely causative variants within HLA-DRB1 as well as within other HLA loci that contribute to disease risk. In addition, more than 100 common variants in non-HLA loci have been implicated in disease susceptibility. Genetic factors are involved not only in the development of RA, but also with various disease subphenotypes, including production and circulating levels of autoantibodies and joint destruction. The major current challenge is to integrate these new data into a precise understanding of disease pathogenesis, including the critical cell types and molecular networks involved as well as interactions with environmental factors. We predict that delineating the functional effects of genetic variants is likely to drive new diagnostic and therapeutic approaches to the disease.

Rare Variants in the Complement Factor H-Related Protein 5 Gene Contribute to Genetic Susceptibility to IgA Nephropathy

A recent genome-wide association study of IgA nephropathy (IgAN) identified 1q32, which contains multiple complement regulatory genes, including the complement factor H (CFH) gene and the complement factor H-related (CFHRs) genes, as an IgAN susceptibility locus. Abnormal complement activation caused by a mutation in CFHR5 was shown to cause CFHR5 nephropathy, which shares many characteristics with IgAN. To explore the genetic effect of variants in CFHR5 on IgAN susceptibility, we recruited 500 patients with IgAN and 576 healthy controls for genetic analysis. We sequenced all exons and their intronic flanking regions as well as the untranslated regions of CFHR5 and compared the frequencies of identified variants using the sequence kernel association test. We identified 32 variants in CFHR5, including 28 rare and four common variants. The distribution of rare variants in CFHR5 in patients with IgAN differed significantly from that in controls (P=0.002). Among the rare variants, in silico programs predicted nine as potential functional variants, which we then assessed in functional assays. Compared with wild-type CFHR5, three recombinant CFHR5 proteins, CFHR5-M (c.508G>A/p.Val170Met), CFHR5-S (c.533A>G/p.Asn178Ser), and CFHR5-D (c.822A>T/p.Glu274Asp), showed significantly higher C3b binding capacity (CFHR5-M: 109.67%±3.54%; P=0.02; CFHR5-S: 174.27%±9.78%; P<0.001; CFHR5-D: 127.25%±1.75%; P<0.001), whereas another recombinant CFHR5 (c.776T>A/p.Leu259Termination) showed less C3b binding (56.89%±0.57%; P<0.001). Our study found that rare variants in CFHR5 may contribute to the genetic susceptibility to IgAN, which suggests that CFHR5 is an IgAN susceptibility gene.

Whole-exome Sequence Analysis Implicates Rare Il17REL Variants in Familial and Sporadic Inflammatory Bowel Disease

BACKGROUND

Rare variants (<1%) likely contribute significantly to risk for common diseases such as inflammatory bowel disease (IBD) in specific patient subsets, such as those with high familiality. They are, however, extraordinarily challenging to identify.

METHODS

To discover candidate rare variants associated with IBD, we performed whole-exome sequencing on 6 members of a pediatric-onset IBD family with multiple affected individuals. To determine whether the variants discovered in this family are also associated with nonfamilial IBD, we investigated their influence on disease in 2 large case-control (CC) series.

RESULTS

We identified 2 rare variants, rs142430606 and rs200958270, both in the established IBD-susceptibility gene IL17REL, carried by all 4 affected family members and their obligate carrier parents. We then demonstrated that both variants are associated with sporadic ulcerative colitis (UC) in 2 independent data sets. For UC in CC 1: rs142430606 (odds ratio [OR] = 2.99, Padj = 0.028; minor allele frequency [MAF]cases = 0.0063, MAFcontrols = 0.0021); rs200958270 (OR = 2.61, Padj = 0.082; MAFcases = 0.0045, MAFcontrols = 0.0017). For UC in CC 2: rs142430606 (OR = 1.94, P = 0.0056; MAFcases = 0.0071, MAFcontrols = 0.0045); rs200958270 (OR = 2.08, P = 0.0028; MAFcases = 0.0071, MAFcontrols = 0.0042).

CONCLUSIONS

We discover in a family and replicate in 2 CC data sets 2 rare susceptibility variants for IBD, both in IL17REL. Our results illustrate that whole-exome sequencing performed on disease-enriched families to guide association testing can be an efficient strategy for the discovery of rare disease-associated variants. We speculate that rare variants identified in families and confirmed in the general population may be important modifiers of disease risk for patients with a family history, and that genetic testing of these variants may be warranted in this patient subset.

The contribution of rare and common variants in 30 genes to risk nicotine dependence

Genetic and functional studies have revealed that both common and rare variants of several nicotinic acetylcholine receptor subunits are associated with nicotine dependence (ND). In this study, we identified variants in 30 candidate genes including nicotinic receptors in 200 sib pairs selected from the Mid-South Tobacco Family population with equal numbers of African Americans (AAs) and European Americans (EAs). We selected 135 of the rare and common variants and genotyped them in the Mid-South Tobacco Case-Control (MSTCC) population, which consists of 3088 AAs and 1430 EAs. None of the genotyped common variants showed significant association with smoking status (smokers vs non-smokers), Fagerström Test for ND scores or indexed cigarettes per day after Bonferroni correction. Rare variants in NRXN1, CHRNA9, CHRNA2, NTRK2, GABBR2, GRIN3A, DNM1, NRXN2, NRXN3 and ARRB2 were significantly associated with smoking status in the MSTCC AA sample, with weighted sum statistic (WSS) P-values ranging from 2.42 × 10(-3) to 1.31 × 10(-4) after 10(6) phenotype rearrangements. We also observed a significant excess of rare nonsynonymous variants exclusive to EA smokers in NRXN1, CHRNA9, TAS2R38, GRIN3A, DBH, ANKK1/DRD2, NRXN3 and CDH13 with WSS P-values between 3.5 × 10(-5) and 1 × 10(-6). Variants rs142807401 (A432T) and rs139982841 (A452V) in CHRNA9 and variants V132L, V389L, rs34755188 (R480H) and rs75981117 (N549S) in GRIN3A are of particular interest because they are found in both the AA and EA samples. A significant aggregate contribution of rare and common coding variants in CHRNA9 to the risk for ND (SKAT-C: P=0.0012) was detected by applying the combined sum test in MSTCC EAs. Together, our results indicate that rare variants alone or combined with common variants in a subset of 30 biological candidate genes contribute substantially to the risk of ND.

Use of next-generation DNA sequencing to analyze genetic variants in rheumatic disease

Next-generation DNA sequencing has revolutionized the field of genetics and genomics, providing researchers with the tools to efficiently identify novel rare and low frequency risk variants, which was not practical with previously available methodologies. These methods allow for the sequence capture of a specific locus or small genetic region all the way up to the entire six billion base pairs of the diploid human genome.

Rheumatic diseases are a huge burden on the US population, affecting more than 46 million Americans. Those afflicted suffer from one or more of the more than 100 diseases characterized by inflammation and loss of function, mainly of the joints, tendons, ligaments, bones, and muscles. While genetics studies of many of these diseases (for example, systemic lupus erythematosus, rheumatoid arthritis, and inflammatory bowel disease) have had major successes in defining their genetic architecture, causal alleles and rare variants have still been elusive. This review describes the current high-throughput DNA sequencing methodologies commercially available and their application to rheumatic diseases in both case–control as well as family-based studies.

Applications of Next-generation Sequencing in Systemic Autoimmune Diseases

Systemic autoimmune diseases are a group of heterogeneous disorders caused by both genetic and environmental factors. Although numerous causal genes have been identified by genome-wide association studies (GWAS), these susceptibility genes are correlated to a relatively low disease risk, indicating that environmental factors also play an important role in the pathogenesis of disease. The intestinal microbiome, as the main symbiotic ecosystem between the host and host-associated microorganisms, has been demonstrated to regulate the development of the body’s immune system and is likely related to genetic mutations in systemic autoimmune diseases. Next-generation sequencing (NGS) technology, with high-throughput capacity and accuracy, provides a powerful tool to discover genomic mutations, abnormal transcription and intestinal microbiome identification for autoimmune diseases. In this review, we briefly outlined the applications of NGS in systemic autoimmune diseases. This review may provide a reference for future studies in the pathogenesis of systemic autoimmune diseases.

MAFsnp: A Multi-Sample Accurate and Flexible SNP Caller Using Next-Generation Sequencing Data

Most existing statistical methods developed for calling single nucleotide polymorphisms (SNPs) using next-generation sequencing (NGS) data are based on Bayesian frameworks, and there does not exist any SNP caller that produces p-values for calling SNPs in a frequentist framework. To fill in this gap, we develop a new method MAFsnp, a Multiple-sample based Accurate and Flexible algorithm for calling SNPs with NGS data. MAFsnp is based on an estimated likelihood ratio test (eLRT) statistic. In practical situation, the involved parameter is very close to the boundary of the parametric space, so the standard large sample property is not suitable to evaluate the finite-sample distribution of the eLRT statistic. Observing that the distribution of the test statistic is a mixture of zero and a continuous part, we propose to model the test statistic with a novel two-parameter mixture distribution. Once the parameters in the mixture distribution are estimated, p-values can be easily calculated for detecting SNPs, and the multiple-testing corrected p-values can be used to control false discovery rate (FDR) at any pre-specified level. With simulated data, MAFsnp is shown to have much better control of FDR than the existing SNP callers. Through the application to two real datasets, MAFsnp is also shown to outperform the existing SNP callers in terms of calling accuracy. An R package "MAFsnp" implementing the new SNP caller is freely available at http://homepage.fudan.edu.cn/zhangh/softwares/.

Investigation of the role of TCF4 rare sequence variants in schizophrenia

Transcription factor 4 (TCF4) is one of the most robust of all reported schizophrenia risk loci and is supported by several genetic and functional lines of evidence. While numerous studies have implicated common genetic variation at TCF4 in schizophrenia risk, the role of rare, small-sized variants at this locus-such as single nucleotide variants and short indels which are below the resolution of chip-based arrays requires further exploration. The aim of the present study was to investigate the association between rare TCF4 sequence variants and schizophrenia. Exon-targeted resequencing was performed in 190 German schizophrenia patients. Six rare variants at the coding exons and flanking sequences of the TCF4 gene were identified, including two missense variants and one splice site variant. These six variants were then pooled with nine additional rare variants identified in 379 European participants of the 1000 Genomes Project, and all 15 variants were genotyped in an independent German sample (n = 1,808 patients; n = 2,261 controls). These data were then analyzed using six statistical methods developed for the association analysis of rare variants. No significant association (P < 0.05) was found. However, the results from our association and power analyses suggest that further research into the possible involvement of rare TCF4 sequence variants in schizophrenia risk is warranted by the assessment of larger cohorts with higher statistical power to identify rare variant associations.

Aggregation of rare/low-frequency variants of the mitochondria respiratory chain-related proteins in rheumatoid arthritis patients

Exome sequencings were conducted using 59 patients having rheumatoid arthritis (RA) and 93 controls. After stepwise filtering, 107 genes showed less than 0.05 of P-values by gene-burden tests. Among 107 genes, NDUFA7 which is a subunit of the complex I in the mitochondrial respiratory chain was selected for further analysis based on previous reports. A case-control study was performed on the three single-nucleotide variants (SNVs) of NDUFA7 with 432 cases and 432 controls. An association was observed between NDUFA7 and RA with severe erosive arthritis. These results together with previous reports suggested the involvement of reactive oxygen species (ROS) in the pathogenesis of RA. In the next step, four SNVs from three genes related to the mitochondrial respiratory chain were selected, which is a major source of ROS, and conducted a case-control study. An association was observed based on a pathway-burden test comprising NDUFA7, SDHAF2, SCO1 and ATP5O: P=1.56E-04, odds ratio=2.16, 95% confidence interval=1.43-3.28. Previous reports suggested the involvement of ROS in the pathogenesis of RA. The aggregation of SNVs in the mitochondria respiratory chain suggests the pivotal role of those SNVs in the pathogenesis of RA with severe erosive arthritis.

Genetics of juvenile idiopathic arthritis: new tools bring new approaches

PURPOSE OF REVIEW

In juvenile idiopathic arthritis (JIA), there are now more than 25 regions represented by single nucleotide polymorphisms that show strong genetic associations. The causal variants and corresponding functions have not yet been defined for the majority of these regions. Here, we review current JIA association findings and the recent progress in the annotation of noncoding portion of the human genome as well as the new technologies necessary to apply this knowledge to JIA association findings.

RECENT FINDINGS

An international collaboration was able to amass sufficient numbers of JIA and control samples to identify significantly robust genetic associations for JIA. The Encyclopedia of DNA Elements project and the National Institutes of Health (NIH) Roadmap Epigenetics Program have now annotated more than 80% of the noncoding genome, important in understanding the impact of risk loci, the majority of which fall outside of protein coding regions. Recent technological advances in high throughput sequencing, chromatin structure determination, transcription factor and enhancer binding site mapping and genome editing will likely provide a basis for understanding JIA genetic risk.

SUMMARY

Understanding the role of genetic variation in the cause of JIA will provide insight for disease mechanism and may explain disease heterogeneity between JIA subtypes and between autoimmune diseases in general.

Association of polymorphisms in interleukin (IL)-12A and -B genes with rheumatoid arthritis in a Chinese population

Rheumatoid arthritis (RA) is characterized by synovial infiltrates and progressive cell-mediated destruction of the joints, which results in significant disability and early mortality. Genetic factors may play an important role in the development of RA. The aim of this study was to investigate the association of common polymorphisms in interleukin (IL)-12A and IL-12B genes with RA in a Chinese Han population. Three single nucleotide polymorphisms (SNPs) in IL-12 genes were genotyped in 412 patients with RA and 279 control subjects using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Our data showed that IL-12B gene SNPs rs3212227 and rs6887695 were observed as a risk factor of RA. The minor allele (C) frequency of IL-12B gene rs3212227 and rs6887695 increased the risk of RA. Individuals carrying the rs3212227/rs6887695 C/C haplotype were associated with a significantly increased risk of RA. RA patients with the C allele of IL-12B gene rs6887695 was a protective factor to erosive arthropathy. Carriers of the C allele of IL-12B gene rs3212227 were significantly more likely to be RF-positive. No significant association was observed between rs2243115 in IL-12A and RA, due probably to the limited power. These results suggest that common variants in IL-12B may contribute to the development of RA in the Chinese population.

Genetic architectures of seropositive and seronegative rheumatic diseases

Rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and some other rheumatic diseases are genetically complex, with evidence of familial clustering, but not of Mendelian inheritance. These diseases are thought to result from contributions and interactions of multiple genetic and nongenetic risk factors, which have small effects individually. Genome-wide association studies (GWAS) of large collections of data from cases and controls have revealed many genetic factors that contribute to non-Mendelian rheumatic diseases, thus providing insights into associated molecular mechanisms. This Review summarizes methods for the identification of gene variants that influence genetically complex diseases and focuses on what we have learned about the rheumatic diseases for which GWAS have been reported. Our review of the disease-associated loci identified to date reveals greater sharing of risk loci among the groups of seropositive (diseases in which specific autoantibodies are often present) or seronegative diseases than between these two groups. The nature of the shared and discordant loci suggests important similarities and differences among these diseases.

Whole-exome SNP array identifies 15 new susceptibility loci for psoriasis

Genome-wide association studies (GWASs) have reproducibly associated ∼40 susceptibility loci with psoriasis. However, the missing heritability is evident and the contributions of coding variants have not yet been systematically evaluated. Here, we present a large-scale whole-exome array analysis for psoriasis consisting of 42,760 individuals. We discover 16 SNPs within 15 new genes/loci associated with psoriasis, including C1orf141, ZNF683, TMC6, AIM2, IL1RL1, CASR, SON, ZFYVE16, MTHFR, CCDC129, ZNF143, AP5B1, SYNE2, IFNGR2 and 3q26.2-q27 (P<5.00 × 10(-08)). In addition, we also replicate four known susceptibility loci TNIP1, NFKBIA, IL12B and LCE3D-LCE3E. These susceptibility variants identified in the current study collectively account for 1.9% of the psoriasis heritability. The variant within AIM2 is predicted to impact protein structure. Our findings increase the number of genetic risk factors for psoriasis and highlight new and plausible biological pathways in psoriasis.

Rare variant association studies: considerations, challenges and opportunities

Genome-wide association studies (GWASs) have successfully uncovered thousands of robust associations between common variants and complex traits and diseases. Despite these successes, much of the heritability of these traits remains unexplained. Because low-frequency and rare variants are not tagged by conventional genome-wide genotyping arrays, they may represent an important and understudied component of complex trait genetics. In contrast to common variant GWASs, there are many different types of study designs, assays and analytic techniques that can be utilized for rare variant association studies (RVASs). In this review, we briefly present the different technologies available to identify rare genetic variants, including novel exome arrays. We also compare the different study designs for RVASs and argue that the best design will likely be phenotype-dependent. We discuss the main analytical issues relevant to RVASs, including the different statistical methods that can be used to test genetic associations with rare variants and the various bioinformatic approaches to predicting in silico biological functions for variants. Finally, we describe recent rare variant association findings, highlighting the unexpected conclusion that most rare variants have modest-to-small effect sizes on phenotypic variation. This observation has major implications for our understanding of the genetic architecture of complex traits in the context of the unexplained heritability challenge.

Identification of rheumatoid arthritis biomarkers based on single nucleotide polymorphisms and haplotype blocks: A systematic review and meta-analysis

Genetics of autoimmune diseases represent a growing domain with surpassing biomarker results with rapid progress. The exact cause of Rheumatoid Arthritis (RA) is unknown, but it is thought to have both a genetic and an environmental bases. Genetic biomarkers are capable of changing the supervision of RA by allowing not only the detection of susceptible individuals, but also early diagnosis, evaluation of disease severity, selection of therapy, and monitoring of response to therapy. This review is concerned with not only the genetic biomarkers of RA but also the methods of identifying them. Many of the identified genetic biomarkers of RA were identified in populations of European and Asian ancestries. The study of additional human populations may yield novel results. Most of the researchers in the field of identifying RA biomarkers use single nucleotide polymorphism (SNP) approaches to express the significance of their results. Although, haplotype block methods are expected to play a complementary role in the future of that field.