Pathogenic Mechanisms in HD datasets, each of them shedding particular light on transcriptional codes and network dynamics in HD. We tested for HD sub-graphs that may be consistently highlighted by several of these mathematical formalisms and whether this may be linked to specific features of the HD process and translate into a more selective level of gene prioritisation. We will present data based on integrating two types of HD networks and discuss how network comparison methods may add value to systems modelling in HD. B48 DNA REPAIR PATHWAYS AS A COMMON GENETIC MECHANISM MODULATING THE AGE AT ONSET IN POLYGLUTAMINE DISEASES ¥1,2 Conceição Bettencourt, ¥3Davina Hensman Moss*, ¥3Michael Flower, Sarah Wiethoff, 5,6Alexis Brice, 7,8Cyril Goizet, 5,9Giovanni Stevanin, 10Georgios Koutsis, 10 Georgia Karadima, 10Marios Panas, 11Petra Yescas-Gómez, 11Lizbeth Esmeralda GarcíaVelázquez, 11María Elisa Alonso-Vilatela, 12,13,14Manuela Lima, 12,13,14Mafalda Raposo, 15 Bryan Traynor, 16Mary Sweeney, 1Nicholas Wood, 1,17Paola Giunti, 5,6Alexandra Durr, for the French SPATAX network, 18Peter Holmans, 1,16Henry Houlden, §3Sarah J Tabrizi, §18 Lesley Jones. 1Department of Molecular Neuroscience, Institute of Neurology, University College London, London , UK; 2Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, UK; 3Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK; 4Centre for Neurology and Hertie Institute for Clinical Brain Research, Eberhard-Karls-University, Tübingen, Germany; 5Inserm U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC University Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), Paris, France; 6APHP, Department of Genetics, University Hospital Pitié-Salpêtrière, Paris, France; 7 Univ. Bordeaux, Laboratoire Maladies Rares: Génétique et Métabolisme, INSERM1211, Bordeaux, France; 8CHU Pellegrin, Service de Génétique Médicale, Bordeaux, France; 9Ecole Pratique des Hautes Etudes, Paris, France; 10Neurogenetics Unit, 1st Department of Neurology, University of Athens Medical School, Eginition Hospital, Athens, Greece; 11 Neurogenetics Department. National Institute of Neurology and Neurosurgery, “Manuel Velasco Suárez”, Mexico City, Mexico; 12Department of Biology, University of the Azores, Ponta Delgada, Portugal; 13Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal; 14Institute for Molecular and Cell Biology (IBMC), University of Porto, Porto, Portugal; 15Laboratory of Neurogenetics, National Institute of Ageing, NIH, Bethesda, MD, USA; 16Neurogenetics Unit, National Hospital for Neurology and Neurosurgery, University College London Hospitals, London, UK; 17Ataxia Centre, Institute of Neurology, University College London, London,UK; 18MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK ¥ These authors contributed equally to this work; §These authors supervised this work ¥1,4 10.1136/jnnp-2016-314597.79 Background Over 30 human diseases are caused by expansion of unstable microsatellite sequences. Nine of these are caused by expanded CAG tracts encoding polyglutamines in different genes. This subgroup of diseases, usually referred to as the polyglutamine diseases which include Huntington’s disease (HD), several spinocerebellar ataxias (SCAs), and spinal and bulbar muscular atrophy, are amongst the commonest hereditary neurodegenerative diseases. Longer CAG repeat tracts are associated with earlier ages at onset (AAO), but this does not account for all the variance, suggesting the existence of additional modifying factors. DNA repair pathways have been recently associated with the HD motor AAO in a recent HD GWAS. We therefore aimed to confirm the association between HD motor AAO and DNA repair pathways; and to investigate whether these modifying effects of variants in DNA repair genes can be extended to other polyglutamine diseases. A26 Methods We collected an independent cohort of 1462 subjects with HD and polyglutamine SCAs, and genotyped SNPs selected from the most significant hits in the HD study. Results In an overall analysis of DNA repair pathway, we found the most significant association with AAO when grouping all polyglutamine diseases (HD+SCAs, p = 1.43 × 10 5). Significant associations were also found for HD (p = 0.00194), all SCAs (p = 0.00107), SCA2 (p = 0.0035), and SCA6 (p = 0.00162). Testing individual SNPs, we found significant associations for rs3512 in FAN1 with HD+SCAs (p = 1.52 × 10 5) and all SCAs (p = 2.22 × 10 4), and rs1805323 in PMS2 with HD+SCAs (p = 3.14 × 10 5). All these associations follow the same direction as in the HD GWAS. Conclusions We show that DNA repair genes significantly modify the AAO not only in HD, but also in polyglutamine SCAs. This suggests a common pathogenic mechanism for these diseases, which could operate through the observed somatic expansion of repeats. Manipulation of DNA repair pathways may offer novel therapeutic opportunities in multiple diseases. B49 GENETIC MODIFIERS OF HUNTINGTON’S DISEASE PROGRESSION **1Davina J Hensman Moss*, **2Antonio F Pardiñas, 1Michael Flower, 2James Miller, Kitty Lo, 4Vincent Plagnol, 2Peter Holmans, 2Lesley Jones, 4Douglas Langbehn, 1Sarah J Tabrizi. 1UCL Institute of Neurology, Department of Neurodegenerative Disease, London, UK; 2Cardiff University, School of Medicine, Cardiff, UK; 3UCL Genetics Institute, Div. of Biosciences, London, UK; 4University of Iowa Carver College of Medicine, Department of Psychiatry and Biostatistics, Iowa, USA **These authors contributed equally to this work 3 10.1136/jnnp-2016-314597.80 Background Huntington’s disease is caused by a CAG repeat expansion; ~60% onset variability is accounted for by age and CAG but studies point to 40% residual heritability. Disease progression offers advantages over age-at-motor onset (AAO) as an analytical phenotype which include use of multiple variables and time-points, and less inter-rater subjectivity. Aims To define accurate stable measures of disease progression in Huntington’s, and use these to identify genetic modifiers. Methods The availability of high quality longitudinal and multivariate data in TRACK-HD enabled us to define rate of progression accurately in 218 subjects. These subjects were then genotyped; imputation then QC generated 9,938,174 variants in 216 subjects. Using mixed-linear models we tested for association with disease progression. To validate our findings we developed a cross-sectional measure of disease progression, and used this to stratify the EHDN REGISTRY cohort. 1,773 subjects with valid phenotype were genotyped, mixed-linear models were used to determine association with cross sectional disease progression. Results We find AAO and progression are correlated, but no evidence of distinct phenotypic clusters: imaging, cognitive, and quantitative-motor measures progress in parallel. In our TRACKHD analysis we identify one significant association (P = 1.92 × 10 8) and one association approaching significance in a gene previously implicated in HD mouse and cell studies (P = 5.82 × 10 8). The TRACK-HD peak in a previously HD-implicated gene was replicated with P = 1.39 × 10 5 in the REGISTRY analysis. Furthermore we found an association (P = 2.90 × 10 7) between J Neurol Neurosurg Psychiatry 2016;87(Suppl 1):A1–A120