Rare and functional SIAE variants are not associated with autoimmune disease risk in up to 66,924 individuals of European ancestry

The effects of pathogenic and likely pathogenic variants for inherited hemostasis disorders in 140 214 UK Biobank participants

Rare genetic diseases affect millions, and identifying causal DNA variants is essential for patient care. Therefore, it is imperative to estimate the effect of each independent variant and improve their pathogenicity classification. Our study of 140 214 unrelated UK Biobank (UKB) participants found that each of them carries a median of 7 variants previously reported as pathogenic or likely pathogenic. We focused on 967 diagnostic-grade gene (DGG) variants for rare bleeding, thrombotic, and platelet disorders (BTPDs) observed in 12 367 UKB participants. By association analysis, for a subset of these variants, we estimated effect sizes for platelet count and volume, and odds ratios for bleeding and thrombosis. Variants causal of some autosomal recessive platelet disorders revealed phenotypic consequences in carriers. Loss-of-function variants in MPL, which cause chronic amegakaryocytic thrombocytopenia if biallelic, were unexpectedly associated with increased platelet counts in carriers. We also demonstrated that common variants identified by genome-wide association studies (GWAS) for platelet count or thrombosis risk may influence the penetrance of rare variants in BTPD DGGs on their associated hemostasis disorders. Network-propagation analysis applied to an interactome of 18 410 nodes and 571 917 edges showed that GWAS variants with large effect sizes are enriched in DGGs and their first-order interactors. Finally, we illustrate the modifying effect of polygenic scores for platelet count and thrombosis risk on disease severity in participants carrying rare variants in TUBB1 or PROC and PROS1, respectively. Our findings demonstrate the power of association analyses using large population datasets in improving pathogenicity classifications of rare variants.

Sialic acid O-acetylation: From biosynthesis to roles in health and disease

Sialic acids are nine-carbon sugars that frequently cap glycans at the cell surface in cells of vertebrates as well as cells of certain types of invertebrates and bacteria. The nine-carbon backbone of sialic acids can undergo extensive enzymatic modification in nature and O-acetylation at the C-4/7/8/9 position in particular is widely observed. In recent years, the detection and analysis of O-acetylated sialic acids have advanced, and sialic acid-specific O-acetyltransferases (SOATs) and O-acetylesterases (SIAEs) that add and remove O-acetyl groups, respectively, have been identified and characterized in mammalian cells, invertebrates, bacteria, and viruses. These advances now allow us to draw a more complete picture of the biosynthetic pathway of the diverse O-acetylated sialic acids to drive the generation of genetically and biochemically engineered model cell lines and organisms with altered expression of O-acetylated sialic acids for dissection of their roles in glycoprotein stability, development, and immune recognition, as well as discovery of novel functions. Furthermore, a growing number of studies associate sialic acid O-acetylation with cancer, autoimmunity, and infection, providing rationale for the development of selective probes and inhibitors of SOATs and SIAEs. Here, we discuss the current insights into the biosynthesis and biological functions of O-acetylated sialic acids and review the evidence linking this modification to disease. Furthermore, we discuss emerging strategies for the design, synthesis, and potential application of unnatural O-acetylated sialic acids and inhibitors of SOATs and SIAEs that may enable therapeutic targeting of this versatile sialic acid modification.

Understanding experiments and research practices for reproducibility: an exploratory study

Scientific experiments and research practices vary across disciplines. The research practices followed by scientists in each domain play an essential role in the understandability and reproducibility of results. The "Reproducibility Crisis", where researchers find difficulty in reproducing published results, is currently faced by several disciplines. To understand the underlying problem in the context of the reproducibility crisis, it is important to first know the different research practices followed in their domain and the factors that hinder reproducibility. We performed an exploratory study by conducting a survey addressed to researchers representing a range of disciplines to understand scientific experiments and research practices for reproducibility. The survey findings identify a reproducibility crisis and a strong need for sharing data, code, methods, steps, and negative and positive results. Insufficient metadata, lack of publicly available data, and incomplete information in study methods are considered to be the main reasons for poor reproducibility. The survey results also address a wide number of research questions on the reproducibility of scientific results. Based on the results of our explorative study and supported by the existing published literature, we offer general recommendations that could help the scientific community to understand, reproduce, and reuse experimental data and results in the research data lifecycle.

Building a Population Representative Pediatric Biobank: Lessons Learned From the Greater Cincinnati Childhood Cohort

Background: Biobanks can accelerate research by providing researchers with samples and data. However, hospital-based recruitment as a source for controls may create bias as who comes to the hospital may be different from the broader population. Methods: In an effort to broadly improve the quality of research studies and reduce costs and challenges associated with recruitment and sample collection, a group of diverse researchers at Cincinnati Children's Hospital Medical Center led an institution-supported initiative to create a population representative pediatric "Greater Cincinnati Childhood Cohort (GCC)." Participants completed a detailed survey, underwent a brief physician-led physical exam, and provided blood, urine, and hair samples. DNA underwent high-throughput genotyping. Results: In total, 1,020 children ages 3-18 years living in the 7 county Greater Cincinnati Metropolitan region were recruited. Racial composition of the cohort was 84% non-Hispanic white, 15% non-Hispanic black, and 2% other race or Hispanic. Participants exhibited marked demographic and disease burden differences by race. Overall, the cohort was broadly used resulting in publications, grants and patents; yet, it did not meet the needs of all potential researchers. Conclusions: Learning from both the strengths and weaknesses, we propose leveraging a community-based participatory research framework for future broad use biobanking efforts.

Whole exome sequencing in a child with acute disseminated encephalomyelitis, optic neuritis, and periodic fever syndrome: a case report

Background

Acute disseminated encephalomyelitis is generally preceded by an infection, and it is usually self-limiting and non-recurrent. However, when there are multiple attacks of acute disseminated encephalomyelitis followed by optic neuritis, it is defined as acute disseminated encephalomyelitis-optic neuritis. To the best of our knowledge, there are no previous reports of acute disseminated encephalomyelitis and optic neuritis preceded by autoinflammation, triggered by periodic fever syndrome.

Case summary

We report on a case of acute disseminated encephalomyelitis with optic neuritis and periodic fever syndrome in a 12-year-old Ecuadorian Hispanic boy with several relapses over the past 10 years, always preceded by autoinflammatory manifestations and without evidence of infectious processes. Whole exome sequencing was performed, and although the results were not conclusive, we found variants in genes associated with both autoinflammatory (NLRP12) and neurological (POLR3A) phenotypes that could be related to the disease pathogenesis having a polygenic rather than monogenic trait.

Conclusion

We propose that an autoinflammatory basis should be pursued in patients diagnosed as having acute disseminated encephalomyelitis and no record of infections. Also, we show that our patient had a good response after 1 year of treatment with low doses of intravenous immunoglobulin and colchicine.

Whole-genome sequencing identifies complex contributions to genetic risk by variants in genes causing monogenic systemic lupus erythematosus

Systemic lupus erythematosus (SLE, OMIM 152700) is a systemic autoimmune disease with a complex etiology. The mode of inheritance of the genetic risk beyond familial SLE cases is currently unknown. Additionally, the contribution of heterozygous variants in genes known to cause monogenic SLE is not fully understood. Whole-genome sequencing of DNA samples from 71 Swedish patients with SLE and their healthy biological parents was performed to investigate the general genetic risk of SLE using known SLE GWAS risk loci identified using the ImmunoChip, variants in genes associated to monogenic SLE, and the mode of inheritance of SLE risk alleles in these families. A random forest model for predicting genetic risk for SLE showed that the SLE risk variants were mainly inherited from one of the parents. In the 71 patients, we detected a significant enrichment of ultra-rare ( ≤ 0.1%) missense and nonsense mutations in 22 genes known to cause monogenic forms of SLE. We identified one previously reported homozygous nonsense mutation in the C1QC (Complement C1q C Chain) gene, which explains the immunodeficiency and severe SLE phenotype of that patient. We also identified seven ultra-rare, coding heterozygous variants in five genes (C1S, DNASE1L3, DNASE1, IFIH1, and RNASEH2A) involved in monogenic SLE. Our findings indicate a complex contribution to the overall genetic risk of SLE by rare variants in genes associated with monogenic forms of SLE. The rare variants were inherited from the other parent than the one who passed on the more common risk variants leading to an increased genetic burden for SLE in the child. Higher frequency SLE risk variants are mostly passed from one of the parents to the offspring affected with SLE. In contrast, the other parent, in seven cases, contributed heterozygous rare variants in genes associated with monogenic forms of SLE, suggesting a larger impact of rare variants in SLE than hitherto reported.

Multiple sclerosis: genetics, biomarkers, treatments

PURPOSE OF REVIEW

We discuss new paradigms for understanding the immunopathology of multiple sclerosis through the recent development of high throughput genetic analysis, emergence of numerous candidate biomarkers, and the broadening of the treatment arsenal.

RECENT FINDINGS

The recent use of genome wide association studies provide new tools for a better understanding of multiple sclerosis etiology. Genome-wide association studies have identified many genes implicated in immune regulation and the next step will be to elucidate how those genetic variations influence immune cell function to drive disease development and progression. Furthermore, patient care has seen the emergence of new biomarkers for monitoring disease progression and response to treatment. Finally, the introduction of numerous immunomodulatory treatments will likely improve clinical outcome of multiple sclerosis patients in the future.

SUMMARY

Breakthroughs in the field of multiple sclerosis have led to a better understanding of the physiopathology of the disease, follow up, and treatment of the patients that develop relapsing remitting multiple sclerosis. The next challenge for multiple sclerosis will be to press forward to model and decipher multiple sclerosis progression, which will help both to develop therapeutics and generate knowledge about mechanisms of neurodegeneration.

Rare variants of the 3'-5' DNA exonuclease TREX1 in early onset small vessel stroke

Background: Monoallelic and biallelic mutations in the exonuclease TREX1 cause monogenic small vessel diseases (SVD). Given recent evidence for genetic and pathophysiological overlap between monogenic and polygenic forms of SVD, evaluation of TREX1 in small vessel stroke is warranted. Methods: We sequenced the TREX1 gene in an exploratory cohort of patients with lacunar stroke (Edinburgh Stroke Study, n=290 lacunar stroke cases). We subsequently performed a fully blinded case-control study of early onset MRI-confirmed small vessel stroke within the UK Young Lacunar Stroke Resource (990 cases, 939 controls). Results: No patients with canonical disease-causing mutations of TREX1 were identified in cases or controls. Analysis of an exploratory cohort identified a potential association between rare variants of TREX1 and patients with lacunar stroke. However, subsequent controlled and blinded evaluation of TREX1 in a larger and MRI-confirmed patient cohort, the UK Young Lacunar Stroke Resource, identified heterozygous rare variants in 2.1% of cases and 2.3% of controls. No association was observed with stroke risk (odds ratio = 0.90; 95% confidence interval, 0.49-1.65 p=0.74). Similarly no association was seen with rare TREX1 variants with predicted deleterious effects on enzyme function (odds ratio = 1.05; 95% confidence interval, 0.43-2.61 p=0.91). Conclusions: No patients with early-onset lacunar stroke had genetic evidence of a TREX1-associated monogenic microangiopathy. These results show no evidence of association between rare variants of TREX1 and early onset lacunar stroke. This includes rare variants that significantly affect protein and enzyme function. Routine sequencing of the TREX1 gene in patients with early onset lacunar stroke is therefore unlikely to be of diagnostic utility, in the absence of syndromic features or family history.

NR1H3 p.Arg415Gln Is Not Associated to Multiple Sclerosis Risk

A recent study by Wang et al. (2016a) claims that the low-frequency variant NR1H3 p.Arg415Gln is sufficient to cause multiple sclerosis in certain individuals and determines a patient's likelihood of primary progressive disease. We sought to replicate this finding in the International MS Genetics Consortium (IMSGC) patient collection, which is 13-fold larger than the collection of Wang et al. (2016a), but we find no evidence that this variant is associated with either MS or disease subtype. Wang et al. (2016a) also report a common variant association in the region, which we show captures the association the IMSGC reported in 2013. Therefore, we conclude that the reported low-frequency association is a false positive, likely generated by insufficient sample size. The claim of NR1H3 mutations describing a Mendelian form of MS-of which no examples exist-can therefore not be substantiated by data. This Matters Arising paper is in response to Wang et al. (2016a), published in Neuron. See also the related Matters Arising paper by Minikel and MacArthur (2016) and the response by Wang et al. (2016b), published in this issue.

SIAE Rare Variants in Juvenile Idiopathic Arthritis and Primary Antibody Deficiencies

Sialic acid acetylesterase (SIAE) deficiency was suggested to lower the levels of ligands for sialic acid-binding immunoglobulin-like receptors, decreasing the threshold for B-cell activation. In humans, studies of rare heterozygous loss-of-function mutations in SIAE gene in common autoimmune diseases, including juvenile idiopathic arthritis (JIA), yielded inconsistent results. Considering the distinct pathogenesis of the two main subtypes of JIA, autoinflammatory systemic (sJIA) and autoimmune oligo/polyarticular (aJIA), and a predisposition to autoimmunity displayed by patients and families with primary antibody deficiencies (PADs), the aim of our study was to analyze whether SIAE rare variants are associated with both the phenotype of JIA and the autoimmunity risk in families with PADs. A cohort of 69 patients with JIA, 117 healthy children, 54 patients, and family members with PADs were enrolled in the study. Three novel SIAE variants (p.Q343P, p.Y495X, and c.1320+33T>C) were found only in patients with aJIA but interestingly also in their healthy relatives without autoimmunity, while none of PAD patients or their relatives carried SIAE defects. Our results show that SIAE rare variants are not causative of autoimmunity as single defects.

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.

Sialic acids and autoimmune disease

An important underlying mechanism that contributes to autoimmunity is the loss of inhibitory signaling in the immune system. Sialic acid-recognizing Ig superfamily lectins or Siglecs are a family of cell surface proteins largely expressed in hematopoietic cells. The majority of Siglecs are inhibitory receptors expressed in immune cells that bind to sialic acid-containing ligands and recruit SH2-domain-containing tyrosine phosphatases to their cytoplasmic tails. They deliver inhibitory signals that can contribute to the constraining of immune cells, and thus protect the host from autoimmunity. The inhibitory functions of CD22/Siglec-2 and Siglec-G and their contributions to tolerance and autoimmunity, primarily in the B lymphocyte context, are considered in some detail in this review. The relevance to autoimmunity and unregulated inflammation of modified sialic acids, enzymes that modify sialic acid, and other sialic acid-binding proteins are also reviewed.

EFHC1 variants in juvenile myoclonic epilepsy: reanalysis according to NHGRI and ACMG guidelines for assigning disease causality

PURPOSE

EFHC1 variants are the most common mutations in inherited myoclonic and grand mal clonic-tonic-clonic (CTC) convulsions of juvenile myoclonic epilepsy (JME). We reanalyzed 54 EFHC1 variants associated with epilepsy from 17 cohorts based on National Human Genome Research Institute (NHGRI) and American College of Medical Genetics and Genomics (ACMG) guidelines for interpretation of sequence variants.

METHODS

We calculated Bayesian LOD scores for variants in coinheritance, unconditional exact tests and odds ratios (OR) in case-control associations, allele frequencies in genome databases, and predictions for conservation/pathogenicity. We reviewed whether variants damage EFHC1 functions, whether efhc1^-/- KO mice recapitulate CTC convulsions and "microdysgenesis" neuropathology, and whether supernumerary synaptic and dendritic phenotypes can be rescued in the fly model when EFHC1 is overexpressed. We rated strengths of evidence and applied ACMG combinatorial criteria for classifying variants.

RESULTS

Nine variants were classified as "pathogenic," 14 as "likely pathogenic," 9 as "benign," and 2 as "likely benign." Twenty variants of unknown significance had an insufficient number of ancestry-matched controls, but ORs exceeded 5 when compared with racial/ethnic-matched Exome Aggregation Consortium (ExAC) controls.

CONCLUSIONS

NHGRI gene-level evidence and variant-level evidence establish EFHC1 as the first non-ion channel microtubule-associated protein whose mutations disturb R-type VDCC and TRPM2 calcium currents in overgrown synapses and dendrites within abnormally migrated dislocated neurons, thus explaining CTC convulsions and "microdysgenesis" neuropathology of JME.Genet Med 19 2, 144-156.

Autoimmune diseases - connecting risk alleles with molecular traits of the immune system

Genome-wide strategies have driven the discovery of more than 300 susceptibility loci for autoimmune diseases. However, for almost all loci, understanding of the mechanisms leading to autoimmunity remains limited, and most variants that are likely to be causal are in non-coding regions of the genome. A critical next step will be to identify the in vivo and ex vivo immunophenotypes that are affected by risk variants. To do this, key cell types and cell states that are implicated in autoimmune diseases will need to be defined. Functional genomic annotations from these cell types and states can then be used to resolve candidate genes and causal variants. Together with longitudinal studies, this approach may yield pivotal insights into how autoimmunity is triggered.

Promises and Pitfalls of High-Throughput Biological Assays

This chapter discusses some of the pitfalls encountered when performing biomedical research involving high-throughput "omics" data and presents some strategies and guidelines that researchers should follow when undertaking such studies. We discuss common errors in experimental design and data analysis that lead to irreproducible and non-replicable research and provide some guidelines to avoid these common mistakes so that researchers may have confidence in study outcomes, even if the results are negative. We discuss the importance of ranking and prespecifying hypotheses, performing power analysis, careful experimental design, and preplanning of statistical analyses in order to avoid the "fishing expedition" data analysis strategy, which is doomed to fail. The impact of multiple testing on false-positive rates is discussed, particularly in the context of the analysis of high-throughput data, and methods to correct for it are presented, as well as approaches to detect and correct for experimental biases and batch effects, which often plague high-throughput assays. We highlight the importance of sharing data and analysis code to facilitate reproducibility and present tools and software that are appropriate for this purpose.

Detection and correction of artefacts in estimation of rare copy number variants and analysis of rare deletions in type 1 diabetes

Copy number variants (CNVs) have been proposed as a possible source of ‘missing heritability’ in complex human diseases. Two studies of type 1 diabetes (T1D) found null associations with common copy number polymorphisms, but CNVs of low frequency and high penetrance could still play a role. We used the Log-R-ratio intensity data from a dense single nucleotide polymorphism (SNP) array, ImmunoChip, to detect rare CNV deletions (rDELs) and duplications (rDUPs) in 6808 T1D cases, 9954 controls and 2206 families with T1D-affected offspring. Initial analyses detected CNV associations. However, these were shown to be false-positive findings, failing replication with polymerase chain reaction. We developed a pipeline of quality control (QC) tests that were calibrated using systematic testing of sensitivity and specificity. The case–control odds ratios (OR) of CNV burden on T1D risk resulting from this QC pipeline converged on unity, suggesting no global frequency difference in rDELs or rDUPs. There was evidence that deletions could impact T1D risk for a small minority of cases, with enrichment for rDELs longer than 400 kb (OR = 1.57, P = 0.005). There were also 18 de novo rDELs detected in affected offspring but none for unaffected siblings (P = 0.03). No specific CNV regions showed robust evidence for association with T1D, although frequencies were lower than expected (most less than 0.1%), substantially reducing statistical power, which was examined in detail. We present an R-package, plumbCNV, which provides an automated approach for QC and detection of rare CNVs that can facilitate equivalent analyses of large-scale SNP array datasets.

Guidelines for investigating causality of sequence variants in human disease

The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.

A systematic approach to assessing the clinical significance of genetic variants

Molecular genetic testing informs diagnosis, prognosis, and risk assessment for patients and their family members. Recent advances in low-cost, high-throughput DNA sequencing and computing technologies have enabled the rapid expansion of genetic test content, resulting in dramatically increased numbers of DNA variants identified per test. To address this challenge, our laboratory has developed a systematic approach to thorough and efficient assessments of variants for pathogenicity determination. We first search for existing data in publications and databases including internal, collaborative and public resources. We then perform full evidence-based assessments through statistical analyses of observations in the general population and disease cohorts, evaluation of experimental data from in vivo or in vitro studies, and computational predictions of potential impacts of each variant. Finally, we weigh all evidence to reach an overall conclusion on the potential for each variant to be disease causing. In this report, we highlight the principles of variant assessment, address the caveats and pitfalls, and provide examples to illustrate the process. By sharing our experience and providing a framework for variant assessment, including access to a freely available customizable tool, we hope to help move towards standardized and consistent approaches to variant assessment.

Multiple sclerosis genetics

Genome-wide association studies have revolutionised the genetic analysis of multiple sclerosis. Through international collaborative efforts involving tens of thousands of cases and controls, more than 100 associated common variants have now been identified. These variants consistently implicate genes associated with immunological processes, overwhelmingly lie in regulatory rather than coding regions, and are frequently associated with other autoimmune diseases. The functional implications of these associated variants are mostly unknown; however, early work has shown that several variants have effects on splicing that result in meaningful changes in the balance between different isoforms in relevant tissues. Including the well established risk attributable to variants in genes encoding human leucocyte antigens, only about a quarter of reported heritability can now be accounted for, suggesting that a substantial potential for further discovery remains.

Rare variants and autoimmune disease

The study of rare variants in monogenic forms of autoimmune disease has offered insight into the aetiology of more complex pathologies. Research in complex autoimmune disease initially focused on sequencing candidate genes, with some early successes, notably in uncovering low-frequency variation associated with Type 1 diabetes mellitus. However, other early examples have proved difficult to replicate, and a recent study across six autoimmune diseases, re-sequencing 25 autoimmune disease-associated genes in large sample sizes, failed to find any associated rare variants. The study of rare and low-frequency variation in autoimmune diseases has been made accessible by the inclusion of such variants on custom genotyping arrays (e.g. Immunochip and Exome arrays). Whole-exome sequencing approaches are now also being utilised to uncover the contribution of rare coding variants to disease susceptibility, severity and treatment response. Other sequencing strategies are starting to uncover the role of regulatory rare variation.

Genome-wide association study of ancestry-specific TB risk in the South African Coloured population

The worldwide burden of tuberculosis (TB) remains an enormous problem, and is particularly severe in the admixed South African Coloured (SAC) population residing in the Western Cape. Despite evidence from twin studies suggesting a strong genetic component to TB resistance, only a few loci have been identified to date. In this work, we conduct a genome-wide association study (GWAS), meta-analysis and trans-ethnic fine mapping to attempt the replication of previously identified TB susceptibility loci. Our GWAS results confirm the WT1 chr11 susceptibility locus (rs2057178: odds ratio = 0.62, P = 2.71e(-06)) previously identified by Thye et al., but fail to replicate previously identified polymorphisms in the TLR8 gene and locus 18q11.2. Our study demonstrates that the genetic contribution to TB risk varies between continental populations, and illustrates the value of including admixed populations in studies of TB risk and other complex phenotypes. Our evaluation of local ancestry based on the real and simulated data demonstrates that case-only admixture mapping is currently impractical in multi-way admixed populations, such as the SAC, due to spurious deviations in average local ancestry generated by current local ancestry inference methods. This study provides insights into identifying disease genes and ancestry-specific disease risk in multi-way admixed populations.

Assessing the validity and reproducibility of genome-scale predictions

MOTIVATION

Validation and reproducibility of results is a central and pressing issue in genomics. Several recent embarrassing incidents involving the irreproducibility of high-profile studies have illustrated the importance of this issue and the need for rigorous methods for the assessment of reproducibility.

RESULTS

Here, we describe an existing statistical model that is very well suited to this problem. We explain its utility for assessing the reproducibility of validation experiments, and apply it to a genome-scale study of adenosine deaminase acting on RNA (ADAR)-mediated RNA editing in Drosophila. We also introduce a statistical method for planning validation experiments that will obtain the tightest reproducibility confidence limits, which, for a fixed total number of experiments, returns the optimal number of replicates for the study.

AVAILABILITY

Downloadable software and a web service for both the analysis of data from a reproducibility study and for the optimal design of these studies is provided at http://ccmbweb.ccv.brown.edu/reproducibility.html .

A novel clinician interface to improve clinician access to up-to-date genetic results

OBJECTIVES

To understand the impact of GeneInsight Clinic (GIC), a web-based tool designed to manage genetic information and facilitate communication of test results and variant updates from the laboratory to the clinics, we measured the use of GIC and the time it took for new genetic knowledge to be available to clinicians.

METHODS

Usage data were collected across four study sites for the GIC launch and post-GIC implementation time periods. The primary outcome measures were the time (average number of days) between variant change approval and notification of clinic staff, and the time between notification and viewing the patient record.

RESULTS

Post-GIC, time between a variant change approval and provider notification was shorter than at launch (average days at launch 503.8, compared to 4.1 days post-GIC). After e-mail alerts were sent at launch, providers clicked into the patient record associated with 91% of these alerts. In the post period, clinic providers clicked into the patient record associated with 95% of the alerts, on average 12 days after the e-mail was sent.

DISCUSSION

We found that GIC greatly increased the likelihood that a provider would receive updated variant information as well as reduced the time associated with distributing that variant information, thus providing a more efficient process for incorporating new genetic knowledge into clinical care.

CONCLUSIONS

Our study results demonstrate that health information technology systems have the potential effectively to assist providers in utilizing genetic information in patient care.

Rethinking mechanisms of autoimmune pathogenesis

Why exactly some individuals develop autoimmune disorders remains unclear. The broadly accepted paradigm is that genetic susceptibility results in some break in immunological tolerance, may enhance the availability of autoantigens, and may enhance inflammatory responses. Some environmental insults that occur on this background of susceptibility may then contribute to autoimmunity. In this review we discuss some aspects related to inhibitory signaling and rare genetic variants, as well as additional factors that might contribute to autoimmunity including the possible role of clonal somatic mutations, the role of epigenetic events and the contribution of the intestinal microbiome. Genetic susceptibility alleles generally contribute to the loss of immunological tolerance, the increased availability of autoantigens, or an increase in inflammation. Apart from common genetic variants, rare loss-of-function genetic variants may also contribute to the pathogenesis of autoimmunity. Studies of an inhibitory signaling pathway in B cells helped identify a negative regulatory enzyme called sialic acid acetyl esterase. The study of rare genetic variants of this enzyme provides an illustrative example showing the importance of detailed functional analyses of variant alleles and the need to exclude functionally normal common or rare genetic variants from analysis. It has also become clear that pathways that are functionally impacted by either common or rare defective variants can also be more significantly compromised by gene expression changes that may result from epigenetic alterations. Another important and evolving area that has been discussed relates to the role of the intestinal microbiome in influencing helper T cell polarization and the development of autoimmunity.

Next-generation sequencing in understanding complex neurological disease

Next-generation sequencing techniques have made vast quantities of data on human genomes and transcriptomes available to researchers. Huge progress has been made towards understanding the basis of many Mendelian neurological conditions, but progress has been considerably slower in complex neurological diseases (multiple sclerosis, migraine, Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and so on). The authors review current next-generation sequencing methodologies and present selected studies illustrating how these have been used to cast light on the genetic etiology of complex neurological diseases with specific focus on multiple sclerosis. The authors highlight particular pitfalls in next-generation sequencing experiments and speculate on both clinical and research applications of these sequencing platforms for complex neurological disorders in the future.

Mapping of immune-mediated disease genes

Genetic studies in immune-mediated diseases have yielded a large number of disease-associated loci. Here we review the progress being made in 12 such diseases, for which 199 independently associated non-HLA loci have been identified by genome-wide association studies since 2007. It is striking that many of the loci are not unique to a single disease but shared between different immune-mediated diseases. The challenge now is to understand how the unique and shared genetic factors can provide insight into the underlying disease biology. We annotated disease-associated variants using the Encyclopedia of DNA Elements (ENCODE) database and demonstrate that, of the predisposing disease variants, the majority have the potential to be regulatory. We also demonstrate that many of these variants affect the expression of nearby genes. Furthermore, we summarize results from the Immunochip, a custom array, which allows a detailed comparison between five of the diseases that have so far been analyzed using this platform.

Gene-function studies in systemic lupus erythematosus

The aetiology of systemic lupus erythematosus (SLE) is complex and is known to involve both genetic and environmental factors. In a small number of patients, single-gene defects can lead to the development of SLE. Such genes include those encoding early components of the complement cascade and the 3'-5' DNA exonuclease TREX1. In addition, genome-wide association studies have identified single-nucleotide polymorphisms that confer some susceptibility to SLE. In this Review, we discuss selected examples of genes whose products have distinctly altered function in SLE and contribute to the pathogenic process. Specifically, we focus on the genes encoding integrin αM (ITGAM), IgG Fc receptors, sialic acid O-acetyl esterase (SIAE), the catalytic subunit of protein phosphatase PP2A (PPP2CA) and signalling lymphocytic activation molecule (SLAM) family members. Moreover, we highlight the changes in epigenetic signatures that occur in SLE. Such epigenetic modifications, which are abundantly present and might alter gene expression in the presence or absence of susceptibility variants, should be carefully considered when deconstructing the contribution of individual genes to the complex pathogenesis of SLE.

M89V Sialic acid Acetyl Esterase (SIAE) and all other non-synonymous common variants of this gene are catalytically normal

Catalytically defective rare variants of Sialic acid Acetyl Esterase (SIAE) have previously been linked to autoimmunity. Studies presented here confirm that the M89V SIAE protein and all other products of common variant alleles of SIAE are catalytically normal. Although overexpressing transfected non-lymphoid cells secrete small amounts of SIAE that can associate with the cell surface, normal human lymphocytes do not exhibit cell surface SIAE, supporting genetic evidence in mice that indicates that this protein functions in a lymphocyte intrinsic manner. Analyses of the plasma proteome also indicate that SIAE is not secreted in vivo. A re-analysis exclusively of catalytically defective rare variant alleles of SIAE in subjects in which this gene was completely sequenced confirmed an association of SIAE with autoimmunity. A subset of catalytically defective rare variant SIAE alleles has previously been typed in a large genotyping study comparing a diverse group of disease subjects and controls; our re-analysis of this data shows that catalytically defective alleles are enriched in disease subjects. These data suggest that SIAE may be associated with autoimmunity and that further study of catalytically defective rare variant SIAE alleles in terms of autoimmune disease susceptibility is strongly warranted.

The role of functionally defective rare germline variants of sialic acid acetylesterase in autoimmune Addison's disease

BACKGROUND

Autoimmune Addison's disease (AAD) is a rare condition with a complex genetic basis. A panel of rare and functionally defective genetic variants in the sialic acid acetylesterase (SIAE) gene has recently been implicated in several common autoimmune conditions. We performed a case-control study to determine whether these rare variants are associated with a rarer condition, AAD.

METHOD

We analysed nine SIAE gene variants (W48X, M89V, C196F, C226G, R230W, T312M, Y349C, F404S and R479C) in a United Kingdom cohort of 378 AAD subjects and 387 healthy controls. All samples were genotyped using Sequenom iPlex chemistry to characterise primer extension products.

RESULTS

A heterozygous rare allele at codon 312 (312*M) was found in one AAD patient (0.13%) but was not detected in the healthy controls. The commoner, functionally recessive variant at codon 89 (89*V) was found to be homozygous in two AAD patients but was only found in the heterozygous state in controls. Taking into account all nine alleles examined, 4/378 (1.06%) AAD patients and 1/387 (0.25%) healthy controls carried the defective SIAE alleles, with a calculated odds ratio of 4.13 (95% CI 0.44-97.45, two-tailed P value 0.212, NS).

CONCLUSION

We demonstrated the presence of 89*V homozygotes and the 312*M rare allele in the AAD cohort, but overall, our analysis does not support a role for rare variants in SIAE in the pathogenesis of AAD. However, the relatively small collection of AAD patients limits the power to exclude a small effect.