DNA methylation classifiers ("episignatures") help to determine the pathogenicity of variants of uncertain significance (VUS). However, their sensitivity is limited due to their training on unambiguous cases with strong-effect variants so that the classification of variants with reduced effect size or in mosaic state may fail. Moreover, episignature evaluation of mosaics as a function of their degree of mosaicism has not been developed so far. We improved episignatures with respect to three categories. Applying (i) minimum-redundancy-maximum-relevance feature selection we reduced their length by up to one order of magnitude without loss of accuracy. Performing (ii) repeated re-training of a support vector machine classifier by step-wise inclusion of cases in the training set that reached probability scores larger than 0.5, we increased the sensitivity of the episignature-classifiers by 30%. In the newly diagnosed patients we confirmed the association between DNA methylation aberration and age at onset of KMT2B-deficient dystonia. Moreover, we found evidence for allelic series, including KMT2B-variants with moderate effects and comparatively mild phenotypes such as late-onset focal dystonia. Retrained classifiers also can detect mosaics that previously remained below the 0.5-threshold, as we showed for KMT2D-associated Kabuki syndrome. Conversely, episignature-classifiers are able to revoke erroneous exome calls of mosaicism, as we demonstrated by (iii) comparing presumed mosaic cases with a distribution of artificial in silico-mosaics that represented all the possible variation in degree of mosaicism, variant read sampling and methylation analysis.

• MeSH
• alely MeSH
• fenotyp MeSH
• lidé MeSH
• metylace DNA * MeSH
• mnohočetné abnormality * genetika   MeSH
• mozaicismus MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

BACKGROUND: Restless legs syndrome is a prevalent chronic neurological disorder with potentially severe mental and physical health consequences. Clearer understanding of the underlying pathophysiology is needed to improve treatment options. We did a meta-analysis of genome-wide association studies (GWASs) to identify potential molecular targets. METHODS: In the discovery stage, we combined three GWAS datasets (EU-RLS GENE, INTERVAL, and 23andMe) with diagnosis data collected from 2003 to 2017, in face-to-face interviews or via questionnaires, and involving 15 126 cases and 95 725 controls of European ancestry. We identified common variants by fixed-effect inverse-variance meta-analysis. Significant genome-wide signals (p≤5 × 10-8) were tested for replication in an independent GWAS of 30 770 cases and 286 913 controls, followed by a joint analysis of the discovery and replication stages. We did gene annotation, pathway, and gene-set-enrichment analyses and studied the genetic correlations between restless legs syndrome and traits of interest. FINDINGS: We identified and replicated 13 new risk loci for restless legs syndrome and confirmed the previously identified six risk loci. MEIS1 was confirmed as the strongest genetic risk factor for restless legs syndrome (odds ratio 1·92, 95% CI 1·85-1·99). Gene prioritisation, enrichment, and genetic correlation analyses showed that identified pathways were related to neurodevelopment and highlighted genes linked to axon guidance (associated with SEMA6D), synapse formation (NTNG1), and neuronal specification (HOXB cluster family and MYT1). INTERPRETATION: Identification of new candidate genes and associated pathways will inform future functional research. Advances in understanding of the molecular mechanisms that underlie restless legs syndrome could lead to new treatment options. We focused on common variants; thus, additional studies are needed to dissect the roles of rare and structural variations. FUNDING: Deutsche Forschungsgemeinschaft, Helmholtz Zentrum München-Deutsches Forschungszentrum für Gesundheit und Umwelt, National Research Institutions, NHS Blood and Transplant, National Institute for Health Research, British Heart Foundation, European Commission, European Research Council, National Institutes of Health, National Institute of Neurological Disorders and Stroke, NIH Research Cambridge Biomedical Research Centre, and UK Medical Research Council.

• MeSH
• běloši MeSH
• celogenomová asociační studie * MeSH
• DNA vazebné proteiny genetika   MeSH
• genetická predispozice k nemoci genetika   MeSH
• GPI-vázané proteiny genetika   MeSH
• lidé MeSH
• netriny MeSH
• proteiny nervové tkáně genetika   MeSH
• semaforiny genetika   MeSH
• syndrom neklidných nohou epidemiologie   genetika   MeSH
• transkripční faktory genetika   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• metaanalýza MeSH
• přehledy MeSH