Analysis of incidental findings in Qatar genome participants reveals novel functional variants in LMNA and DSP.

In order to report clinically actionable incidental findings in genetic testing, the American College of Medical Genetics and Genomics (ACMG) recommended the evaluation of variants in 59 genes associated with highly penetrant mutations. However, there is a lack of epidemiological data on medically actionable rare variants in these genes in Arab populations. We used whole genome sequencing data from 6045 participants from the Qatar Genome Programme and integrated it with phenotypic data collected by the Qatar Biobank. We identified novel putative pathogenic variants in the 59 ACMG genes by filtering previously unrecorded variants based on computational prediction of pathogenicity, variant rarity and segregation evidence. We assessed the phenotypic associations of candidate variants in genes linked to cardiovascular diseases. Finally, we used a zebrafish knockdown and synthetic human mRNA co-injection assay to functionally characterize two of these novel variants. We assessed the zebrafish cardiac function in terms of heart rate, rhythm and hemodynamics, as well as the heart structure. We identified 52 492 novel variants, which have not been reported in global and disease-specific databases. A total of 74 novel variants were selected with potentially pathogenic effect. We prioritized two novel cardiovascular variants, DSP c.1841A > G (p.Asp614Gly) and LMNA c.326 T > G (p.Val109Gly) for functional characterization. Our results showed that both variants resulted in abnormal zebrafish heart rate, rhythm and structure. This study highlights medically actionable variants that are specific to the Middle Eastern Qatari population.

Genome sequencing data analysis for rare disease gene discovery.

Rare diseases occur in a smaller proportion of the general population, which is variedly defined as less than 200 000 individuals (US) or in less than 1 in 2000 individuals (Europe). Although rare, they collectively make up to approximately 7000 different disorders, with majority having a genetic origin, and affect roughly 300 million people globally. Most of the patients and their families undergo a long and frustrating diagnostic odyssey. However, advances in the field of genomics have started to facilitate the process of diagnosis, though it is hindered by the difficulty in genome data analysis and interpretation. A major impediment in diagnosis is in the understanding of the diverse approaches, tools and datasets available for variant prioritization, the most important step in the analysis of millions of variants to select a few potential variants. Here we present a review of the latest methodological developments and spectrum of tools available for rare disease genetic variant discovery and recommend appropriate data interpretation methods for variant prioritization. We have categorized the resources based on various steps of the variant interpretation workflow, starting from data processing, variant calling, annotation, filtration and finally prioritization, with a special emphasis on the last two steps. The methods discussed here pertain to elucidating the genetic basis of disease in individual patient cases via trio- or family-based analysis of the genome data. We advocate the use of a combination of tools and datasets and to follow multiple iterative approaches to elucidate the potential causative variant.

Efficient and flexible Integration of variant characteristics in rare variant association studies using integrated nested Laplace approximation.

Rare variants are thought to play an important role in the etiology of complex diseases and may explain a significant fraction of the missing heritability in genetic disease studies. Next-generation sequencing facilitates the association of rare variants in coding or regulatory regions with complex diseases in large cohorts at genome-wide scale. However, rare variant association studies (RVAS) still lack power when cohorts are small to medium-sized and if genetic variation explains a small fraction of phenotypic variance. Here we present a novel Bayesian rare variant Association Test using Integrated Nested Laplace Approximation (BATI). Unlike existing RVAS tests, BATI allows integration of individual or variant-specific features as covariates, while efficiently performing inference based on full model estimation. We demonstrate that BATI outperforms established RVAS methods on realistic, semi-synthetic whole-exome sequencing cohorts, especially when using meaningful biological context, such as functional annotation. We show that BATI achieves power above 70% in scenarios in which competing tests fail to identify risk genes, e.g. when risk variants in sum explain less than 0.5% of phenotypic variance. We have integrated BATI, together with five existing RVAS tests in the 'Rare Variant Genome Wide Association Study' (rvGWAS) framework for data analyzed by whole-exome or whole genome sequencing. rvGWAS supports rare variant association for genes or any other biological unit such as promoters, while allowing the analysis of essential functionalities like quality control or filtering. Applying rvGWAS to a Chronic Lymphocytic Leukemia study we identified eight candidate predisposition genes, including EHMT2 and COPS7A.

Functional Characterization of the MYO6 Variant p.E60Q in Non-Syndromic Hearing Loss Patients.

Hereditary hearing loss (HHL) is a common genetic disorder accounting for at least 60% of pre-lingual deafness in children, of which 70% is inherited in an autosomal recessive pattern. The long tradition of consanguinity among the Qatari population has increased the prevalence of HHL, which negatively impacts the quality of life. Here, we functionally validated the pathogenicity of the c.178G>C, p.E60Q mutation in the MYO6 gene, which was detected previously in a Qatari HHL family, using cellular and animal models. In vitro analysis was conducted in HeLa cells transiently transfected with plasmids carrying MYO6WT or MYO6p.E60Q, and a zebrafish model was generated to characterize the in vivo phenotype. Cells transfected with MYO6WT showed higher expression of MYO6 in the plasma membrane and increased ATPase activity. Modeling the human MYO6 variants in zebrafish resulted in severe otic defects. At 72 h post-injection, MYO6p.E60Q embryos demonstrated alterations in the sizes of the saccule and utricle. Additionally, zebrafish with MYO6p.E60Q displayed super-coiled and bent hair bundles in otic hair cells when compared to control and MYO6WT embryos. In conclusion, our cellular and animal models add support to the in silico prediction that the p.E60Q missense variant is pathogenic and damaging to the protein. Since the c.178G>C MYO6 variant has a 0.5% allele frequency in the Qatari population, about 400 times higher than in other populations, it could contribute to explaining the high prevalence of hearing impairment in Qatar.

Actionable genomic variants in 6045 participants from the Qatar Genome Program.

In a clinical setting, DNA sequencing can uncover findings unrelated to the purpose of genetic evaluation. The American College of Medical Genetics and Genomics (ACMG) recommends the evaluation and reporting of 59 genes from clinic genomic sequencing. While the prevalence of secondary findings is available from large population studies, these data lack Arab and other Middle Eastern populations. The Qatar Genome Program (QGP) generates whole-genome sequencing (WGS) data and combines it with phenotypic information to create a comprehensive database for studying the Qatari and wider Arab and Middle Eastern populations at the molecular level. This study identified and analyzed medically actionable variants in the 59 ACMG genes using WGS data from 6045 QGP participants. Our results identified a total of 60 pathogenic and likely pathogenic variants in 25 ACMG genes in 141 unique individuals. Overall, 2.3% of the QGP sequenced participants carried a pathogenic or likely pathogenic variant in one of the 59 ACMG genes. We evaluated the QGP phenotype-genotype association of additional nonpathogenic ACMG variants. These variants were found in patients from the Hamad Medical Corporation or reported incidental findings data in Qatar. We found a significant phenotype association for two variants, c.313+3A>C in LDLR, and c.58C>T (p.Gln20*) in the TPM1.

Variability of multi-omics profiles in a population-based child cohort.

BACKGROUND: Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood. METHODS: We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability. RESULTS: All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability. CONCLUSIONS: Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both.

Cell type-specific novel long non-coding RNA and circular RNA in the BLUEPRINT hematopoietic transcriptomes atlas.

Transcriptional profiling of hematopoietic cell subpopulations has helped to characterize the developmental stages of the hematopoietic system and the molecular bases of malignant and non-malignant blood diseases. Previously, only the genes targeted by expression microarrays could be profiled genome-wide. High-throughput RNA sequencing, however, encompasses a broader repertoire of RNA molecules, without restriction to previously annotated genes. We analyzed the BLUEPRINT consortium RNA-sequencing data for mature hematopoietic cell types. The data comprised 90 total RNA-sequencing samples, each composed of one of 27 cell types, and 32 small RNA-sequencing samples, each composed of one of 11 cell types. We estimated gene and isoform expression levels for each cell type using existing annotations from Ensembl. We then used guided transcriptome assembly to discover unannotated transcripts. We identified hundreds of novel non-coding RNA genes and showed that the majority have cell type-dependent expression. We also characterized the expression of circular RNA and found that these are also cell type-specific. These analyses refine the active transcriptional landscape of mature hematopoietic cells, highlight abundant genes and transcriptional isoforms for each blood cell type, and provide a valuable resource for researchers of hematologic development and diseases. Finally, we made the data accessible via a web-based interface: https://blueprint.haem.cam.ac.uk/bloodatlas/.

Non-coding recurrent mutations in chronic lymphocytic leukaemia.

Chronic lymphocytic leukaemia (CLL) is a frequent disease in which the genetic alterations determining the clinicobiological behaviour are not fully understood. Here we describe a comprehensive evaluation of the genomic landscape of 452 CLL cases and 54 patients with monoclonal B-lymphocytosis, a precursor disorder. We extend the number of CLL driver alterations, including changes in ZNF292, ZMYM3, ARID1A and PTPN11. We also identify novel recurrent mutations in non-coding regions, including the 3' region of NOTCH1, which cause aberrant splicing events, increase NOTCH1 activity and result in a more aggressive disease. In addition, mutations in an enhancer located on chromosome 9p13 result in reduced expression of the B-cell-specific transcription factor PAX5. The accumulative number of driver alterations (0 to ≥4) discriminated between patients with differences in clinical behaviour. This study provides an integrated portrait of the CLL genomic landscape, identifies new recurrent driver mutations of the disease, and suggests clinical interventions that may improve the management of this neoplasia.

Mutations in DCHS1 cause mitral valve prolapse.

Mitral valve prolapse (MVP) is a common cardiac valve disease that affects nearly 1 in 40 individuals. It can manifest as mitral regurgitation and is the leading indication for mitral valve surgery. Despite a clear heritable component, the genetic aetiology leading to non-syndromic MVP has remained elusive. Four affected individuals from a large multigenerational family segregating non-syndromic MVP underwent capture sequencing of the linked interval on chromosome 11. We report a missense mutation in the DCHS1 gene, the human homologue of the Drosophila cell polarity gene dachsous (ds), that segregates with MVP in the family. Morpholino knockdown of the zebrafish homologue dachsous1b resulted in a cardiac atrioventricular canal defect that could be rescued by wild-type human DCHS1, but not by DCHS1 messenger RNA with the familial mutation. Further genetic studies identified two additional families in which a second deleterious DCHS1 mutation segregates with MVP. Both DCHS1 mutations reduce protein stability as demonstrated in zebrafish, cultured cells and, notably, in mitral valve interstitial cells (MVICs) obtained during mitral valve repair surgery of a proband. Dchs1(+/-) mice had prolapse of thickened mitral leaflets, which could be traced back to developmental errors in valve morphogenesis. DCHS1 deficiency in MVP patient MVICs, as well as in Dchs1(+/-) mouse MVICs, result in altered migration and cellular patterning, supporting these processes as aetiological underpinnings for the disease. Understanding the role of DCHS1 in mitral valve development and MVP pathogenesis holds potential for therapeutic insights for this very common disease.

International Cooperation to Enable the Diagnosis of All Rare Genetic Diseases.

Provision of a molecularly confirmed diagnosis in a timely manner for children and adults with rare genetic diseases shortens their "diagnostic odyssey," improves disease management, and fosters genetic counseling with respect to recurrence risks while assuring reproductive choices. In a general clinical genetics setting, the current diagnostic rate is approximately 50%, but for those who do not receive a molecular diagnosis after the initial genetics evaluation, that rate is much lower. Diagnostic success for these more challenging affected individuals depends to a large extent on progress in the discovery of genes associated with, and mechanisms underlying, rare diseases. Thus, continued research is required for moving toward a more complete catalog of disease-related genes and variants. The International Rare Diseases Research Consortium (IRDiRC) was established in 2011 to bring together researchers and organizations invested in rare disease research to develop a means of achieving molecular diagnosis for all rare diseases. Here, we review the current and future bottlenecks to gene discovery and suggest strategies for enabling progress in this regard. Each successful discovery will define potential diagnostic, preventive, and therapeutic opportunities for the corresponding rare disease, enabling precision medicine for this patient population.

Severe Autoinflammatory Manifestations and Antibody Deficiency Due to Novel Hypermorphic PLCG2 Mutations.

Autoinflammatory diseases (AIDs) were first described as clinical disorders characterized by recurrent episodes of seemingly unprovoked sterile inflammation. In the past few years, the identification of novel AIDs expanded their phenotypes toward more complex clinical pictures associating vasculopathy, autoimmunity, or immunodeficiency. Herein, we describe two unrelated patients suffering since the neonatal period from a complex disease mainly characterized by severe sterile inflammation, recurrent bacterial infections, and marked humoral immunodeficiency. Whole-exome sequencing detected a novel, de novo heterozygous PLCG2 variant in each patient (p.Ala708Pro and p.Leu845_Leu848del). A clear enhanced PLCγ2 activity for both variants was demonstrated by both ex vivo calcium responses of the patient's B cells to IgM stimulation and in vitro assessment of PLC activity. These data supported the autoinflammation and PLCγ2-associated antibody deficiency and immune dysregulation (APLAID) diagnosis in both patients. Immunological evaluation revealed a severe decrease of immunoglobulins and B cells, especially class-switched memory B cells, with normal T and NK cell counts. Analysis of bone marrow of one patient revealed a reduced immature B cell fraction compared with controls. Additional investigations showed that both PLCG2 variants activate the NLRP3-inflammasome through the alternative pathway instead of the canonical pathway. Collectively, the evidences here shown expand APLAID diversity toward more severe phenotypes than previously reported including dominantly inherited agammaglobulinemia, add novel data about its genetic basis, and implicate the alternative NLRP3-inflammasome activation pathway in the basis of sterile inflammation.

In utero and childhood exposure to tobacco smoke and multi-layer molecular signatures in children.

BACKGROUND: The adverse health effects of early life exposure to tobacco smoking have been widely reported. In spite of this, the underlying molecular mechanisms of in utero and postnatal exposure to tobacco smoke are only partially understood. Here, we aimed to identify multi-layer molecular signatures associated with exposure to tobacco smoke in these two exposure windows. METHODS: We investigated the associations of maternal smoking during pregnancy and childhood secondhand smoke (SHS) exposure with molecular features measured in 1203 European children (mean age 8.1 years) from the Human Early Life Exposome (HELIX) project. Molecular features, covering 4 layers, included blood DNA methylation and gene and miRNA transcription, plasma proteins, and sera and urinary metabolites. RESULTS: Maternal smoking during pregnancy was associated with DNA methylation changes at 18 loci in child blood. DNA methylation at 5 of these loci was related to expression of the nearby genes. However, the expression of these genes themselves was only weakly associated with maternal smoking. Conversely, childhood SHS was not associated with blood DNA methylation or transcription patterns, but with reduced levels of several serum metabolites and with increased plasma PAI1 (plasminogen activator inhibitor-1), a protein that inhibits fibrinolysis. Some of the in utero and childhood smoking-related molecular marks showed dose-response trends, with stronger effects with higher dose or longer duration of the exposure. CONCLUSION: In this first study covering multi-layer molecular features, pregnancy and childhood exposure to tobacco smoke were associated with distinct molecular phenotypes in children. The persistent and dose-dependent changes in the methylome make CpGs good candidates to develop biomarkers of past exposure. Moreover, compared to methylation, the weak association of maternal smoking in pregnancy with gene expression suggests different reversal rates and a methylation-based memory to past exposures. Finally, certain metabolites and protein markers evidenced potential early biological effects of postnatal SHS, such as fibrinolysis.

Allele balance bias identifies systematic genotyping errors and false disease associations.

In recent years, next-generation sequencing (NGS) has become a cornerstone of clinical genetics and diagnostics. Many clinical applications require high precision, especially if rare events such as somatic mutations in cancer or genetic variants causing rare diseases need to be identified. Although random sequencing errors can be modeled statistically and deep sequencing minimizes their impact, systematic errors remain a problem even at high depth of coverage. Understanding their source is crucial to increase precision of clinical NGS applications. In this work, we studied the relation between recurrent biases in allele balance (AB), systematic errors, and false positive variant calls across a large cohort of human samples analyzed by whole exome sequencing (WES). We have modeled the AB distribution for biallelic genotypes in 987 WES samples in order to identify positions recurrently deviating significantly from the expectation, a phenomenon we termed allele balance bias (ABB). Furthermore, we have developed a genotype callability score based on ABB for all positions of the human exome, which detects false positive variant calls that passed state-of-the-art filters. Finally, we demonstrate the use of ABB for detection of false associations proposed by rare variant association studies. Availability: https://github.com/Francesc-Muyas/ABB.

eDiVA-Classification and prioritization of pathogenic variants for clinical diagnostics.

Mendelian diseases have shown to be an and efficient model for connecting genotypes to phenotypes and for elucidating the function of genes. Whole-exome sequencing (WES) accelerated the study of rare Mendelian diseases in families, allowing for directly pinpointing rare causal mutations in genic regions without the need for linkage analysis. However, the low diagnostic rates of 20-30% reported for multiple WES disease studies point to the need for improved variant pathogenicity classification and causal variant prioritization methods. Here, we present the exome Disease Variant Analysis (eDiVA; http://ediva.crg.eu), an automated computational framework for identification of causal genetic variants (coding/splicing single-nucleotide variants and small insertions and deletions) for rare diseases using WES of families or parent-child trios. eDiVA combines next-generation sequencing data analysis, comprehensive functional annotation, and causal variant prioritization optimized for familial genetic disease studies. eDiVA features a machine learning-based variant pathogenicity predictor combining various genomic and evolutionary signatures. Clinical information, such as disease phenotype or mode of inheritance, is incorporated to improve the precision of the prioritization algorithm. Benchmarking against state-of-the-art competitors demonstrates that eDiVA consistently performed as a good or better than existing approach in terms of detection rate and precision. Moreover, we applied eDiVA to several familial disease cases to demonstrate its clinical applicability.

Detailed analysis of inversions predicted between two human genomes: errors, real polymorphisms, and their origin and population distribution.

The growing catalogue of structural variants in humans often overlooks inversions as one of the most difficult types of variation to study, even though they affect phenotypic traits in diverse organisms. Here, we have analysed in detail 90 inversions predicted from the comparison of two independently assembled human genomes: the reference genome (NCBI36/HG18) and HuRef. Surprisingly, we found that two thirds of these predictions (62) represent errors either in assembly comparison or in one of the assemblies, including 27 misassembled regions in HG18. Next, we validated 22 of the remaining 28 potential polymorphic inversions using different PCR techniques and characterized their breakpoints and ancestral state. In addition, we determined experimentally the derived allele frequency in Europeans for 17 inversions (DAF = 0.01-0.80), as well as the distribution in 14 worldwide populations for 12 of them based on the 1000 Genomes Project data. Among the validated inversions, nine have inverted repeats (IRs) at their breakpoints, and two show nucleotide variation patterns consistent with a recurrent origin. Conversely, inversions without IRs have a unique origin and almost all of them show deletions or insertions at the breakpoints in the derived allele mediated by microhomology sequences, which highlights the importance of mechanisms like FoSTeS/MMBIR in the generation of complex rearrangements in the human genome. Finally, we found several inversions located within genes and at least one candidate to be positively selected in Africa. Thus, our study emphasizes the importance of careful analysis and validation of large-scale genomic predictions to extract reliable biological conclusions.

Survey of 800+ data sets from human tissue and body fluid reveals xenomiRs are likely artifacts.

miRNAs are small 22-nucleotide RNAs that can post-transcriptionally regulate gene expression. It has been proposed that dietary plant miRNAs can enter the human bloodstream and regulate host transcripts; however, these findings have been widely disputed. We here conduct the first comprehensive meta-study in the field, surveying the presence and abundances of cross-species miRNAs (xenomiRs) in 824 sequencing data sets from various human tissues and body fluids. We find that xenomiRs are commonly present in tissues (17%) and body fluids (69%); however, the abundances are low, comprising 0.001% of host human miRNA counts. Further, we do not detect a significant enrichment of xenomiRs in sequencing data originating from tissues and body fluids that are exposed to dietary intake (such as liver). Likewise, there is no significant depletion of xenomiRs in tissues and body fluids that are relatively separated from the main bloodstream (such as brain and cerebro-spinal fluids). Interestingly, the majority (81%) of body fluid xenomiRs stem from rodents, which are a rare human dietary contribution but common laboratory animals. Body fluid samples from the same studies tend to group together when clustered by xenomiR compositions, suggesting technical batch effects. Last, we performed carefully designed and controlled animal feeding studies, in which we detected no transfer of plant miRNAs into rat blood, or bovine milk sequences into piglet blood. In summary, our comprehensive computational and experimental results indicate that xenomiRs originate from technical artifacts rather than dietary intake.

A genome-wide association meta-analysis of diarrhoeal disease in young children identifies FUT2 locus and provides plausible biological pathways.

More than a million childhood diarrhoeal episodes occur worldwide each year, and in developed countries a considerable part of them are caused by viral infections. In this study, we aimed to search for genetic variants associated with diarrhoeal disease in young children by meta-analyzing genome-wide association studies, and to elucidate plausible biological mechanisms. The study was conducted in the context of the Early Genetics and Lifecourse Epidemiology (EAGLE) consortium. Data about diarrhoeal disease in two time windows (around 1 year of age and around 2 years of age) was obtained via parental questionnaires, doctor interviews or medical records. Standard quality control and statistical tests were applied to the 1000 Genomes imputed genotypic data. The meta-analysis (N = 5758) followed by replication (N = 3784) identified a genome-wide significant association between rs8111874 and diarrhoea at age 1 year. Conditional analysis suggested that the causal variant could be rs601338 (W154X) in the FUT2 gene. Children with the A allele, which results in a truncated FUT2 protein, had lower risk of diarrhoea. FUT2 participates in the production of histo-blood group antigens and has previously been implicated in the susceptibility to infections, including Rotavirus and Norovirus Gene-set enrichment analysis suggested pathways related to the histo-blood group antigen production, and the regulation of ion transport and blood pressure. Among others, the gastrointestinal tract, and the immune and neuro-secretory systems were detected as relevant organs. In summary, this genome-wide association meta-analysis suggests the implication of the FUT2 gene in diarrhoeal disease in young children from the general population.

HLA-DRB1*11 and variants of the MHC class II locus are strong risk factors for systemic juvenile idiopathic arthritis.

Systemic juvenile idiopathic arthritis (sJIA) is an often severe, potentially life-threatening childhood inflammatory disease, the pathophysiology of which is poorly understood. To determine whether genetic variation within the MHC locus on chromosome 6 influences sJIA susceptibility, we performed an association study of 982 children with sJIA and 8,010 healthy control subjects from nine countries. Using meta-analysis of directly observed and imputed SNP genotypes and imputed classic HLA types, we identified the MHC locus as a bona fide susceptibility locus with effects on sJIA risk that transcended geographically defined strata. The strongest sJIA-associated SNP, rs151043342 [P = 2.8 × 10(-17), odds ratio (OR) 2.6 (2.1, 3.3)], was part of a cluster of 482 sJIA-associated SNPs that spanned a 400-kb region and included the class II HLA region. Conditional analysis controlling for the effect of rs151043342 found that rs12722051 independently influenced sJIA risk [P = 1.0 × 10(-5), OR 0.7 (0.6, 0.8)]. Meta-analysis of imputed classic HLA-type associations in six study populations of Western European ancestry revealed that HLA-DRB1*11 and its defining amino acid residue, glutamate 58, were strongly associated with sJIA [P = 2.7 × 10(-16), OR 2.3 (1.9, 2.8)], as was the HLA-DRB1*11-HLA-DQA1*05-HLA-DQB1*03 haplotype [6.4 × 10(-17), OR 2.3 (1.9, 2.9)]. By examining the MHC locus in the largest collection of sJIA patients assembled to date, this study solidifies the relationship between the class II HLA region and sJIA, implicating adaptive immune molecules in the pathogenesis of sJIA.

Geolocalisation of athletes for out-of-competition drug testing: ethical considerations. Position statement by the WADA Ethics Panel.

Through the widespread availability of location-identifying devices, geolocalisation could potentially be used to place athletes during out-of-competition testing. In light of this debate, the WADA Ethics Panel formulated the following questions: (1) should WADA and/or other sponsors consider funding such geolocalisation research projects?, (2) if successful, could they be proposed to athletes as a complementary device to Anti-Doping Administration and Management System to help geolocalisation and reduce the risk of missed tests? and (3) should such devices be offered on a voluntary basis, or is it conceivable that they would be made mandatory for all athletes in registered testing pools? In this position paper, the WADA Ethics Panel concludes that the use of geolocalisation could be useful in a research setting with the goal of understanding associations between genotype, phenotype and environment; however, it recognises that the use of geolocalisation as part of or as replacement of whereabouts rules is replete with ethical concerns. While benefits remain largely hypothetical and minimal, the potential invasion of privacy and the data security threats are real. Considering the impact on privacy, data security issues, the societal ramifications of offering such services and various pragmatic considerations, the WADA Ethics Panel concludes that at this time, the use of geolocalisation should neither be mandated as a tool for disclosing whereabouts nor implemented on a voluntary basis.

Missense mutations in TENM4, a regulator of axon guidance and central myelination, cause essential tremor.

Essential tremor (ET) is a common movement disorder with an estimated prevalence of 5% of the population aged over 65 years. In spite of intensive efforts, the genetic architecture of ET remains unknown. We used a combination of whole-exome sequencing and targeted resequencing in three ET families. In vitro and in vivo experiments in oligodendrocyte precursor cells and zebrafish were performed to test our findings. Whole-exome sequencing revealed a missense mutation in TENM4 segregating in an autosomal-dominant fashion in an ET family. Subsequent targeted resequencing of TENM4 led to the discovery of two novel missense mutations. Not only did these two mutations segregate with ET in two additional families, but we also observed significant over transmission of pathogenic TENM4 alleles across the three families. Consistent with a dominant mode of inheritance, in vitro analysis in oligodendrocyte precursor cells showed that mutant proteins mislocalize. Finally, expression of human mRNA harboring any of three patient mutations in zebrafish embryos induced defects in axon guidance, confirming a dominant-negative mode of action for these mutations. Our genetic and functional data, which is corroborated by the existence of a Tenm4 knockout mouse displaying an ET phenotype, implicates TENM4 in ET. Together with previous studies of TENM4 in model organisms, our studies intimate that processes regulating myelination in the central nervous system and axon guidance might be significant contributors to the genetic burden of this disorder.