Leveraging the power of genomics and transcriptomics to revolutionise the diagnosis and understanding of neurological disorders

在神经系统疾病患者中存在巨大的未满足需求。不可避免地，这导致了基因组学英格兰NHS 100，000基因组（100 K）项目中非常高的神经学特异性招募。患有神经系统疾病的家庭占迄今为止在10万人中进行的所有基因组测序（WGS）的24.1%，共计来自6，807个家庭的13，326人。目前，来自每个家庭的受影响个体由100 K团队筛查已知的诊断基因，但只有大约20%的患者获得诊断，这仍然使80%的家庭没有确定的遗传原因，需要进一步调查。按照目前的速度，到项目结束时，我们预计将拥有超过15，000个基因组和超过8，000个家族的队列。基因组分析的主要挑战是WGS发现遗传变异的能力大大超过了我们解释其功能和临床影响的能力。我们处于独特的地位，可以利用100 K项目提供的机会来研究神经退行性疾病，原因是：a）大量神经病学先证者和家庭成员的基因组测序，B）NHS医疗保健系统的独特性质，使我们能够跟踪患者并获得与每个样本相关的大量临床信息，这些信息对于变异解释至关重要，c）从先证者和亲属那里收集生物样本，以便进行下游生物学分析; d）10万NHS同意每年最多四次回到家庭进行进一步的研究需求，大多数神经学家庭都在我们的机构，这对于更深入的表型和进一步的样本将是重要的。作为一个团队，我们已经在神经遗传学方面有了令人印象深刻的记录。我们已经使用WGS数据来识别和鉴定广泛的突变类型和疾病基因，包括点突变，基因组重复和缺失，新的从头和镶嵌突变，我们重新注释了新发现的表达非编码区，以及最近未发表的导致共济失调的新型重复扩展（参见案例中的初步数据以获得支持）。我们将在本提案中应用综合分析方法，通过调查和鉴定100 K中未诊断的神经系统疾病的基因组异常，专注于遗传性神经退行性疾病，并将其与收集的临床数据相结合。我们将识别大量潜在的致病性变异，并使用大脑转录组数据优化变异注释和优先排序。我们将使用RNA测序来进一步提高诊断率，通过我们的研究和合作获得额外的测序疾病队列将提高我们验证新疾病基因致病性和扩大疾病表型的能力。使用这种方法，我们将确定负责特定表型的新基因和共同机制，这些表型对孟德尔和非家族性神经退行性疾病的谱有影响。这也将使我们能够根据WGS的使用和对分子机制的深入理解重新确定神经退行性疾病的分类，而不是目前使用的传统的“主要表型”方法。该提案非常及时，整个100 K WGS数据集将于2018年12月31日完全发布。我们的方法将提高我们诊断新的神经系统疾病的能力，同时也将确定疾病的新机制和途径。遗传性和侵袭性疾病可能涉及关键细胞通路的缺陷，涉及与许多形式的常见神经退行性疾病相关的机制，这些机制将支持目前无法治愈的疾病的治疗方法的发展。

There is a huge unmet need amongst patients with neurological disorders. Inevitably, this has led to very high neurology-specific recruitment within the Genomics England NHS 100,000 genomes (100K) project. Families with neurological disorders account for 24.1% of all genome sequencing (WGS) carried out in the 100K so far, amounting to 13,326 individuals from 6,807 families. At present affected individuals from each of these families are screened for the known diagnostic genes by the 100K team, but only around 20% of patients gain a diagnosis, this still leaves 80% of families with no genetic cause identified that require further investigation. At current rates, by the end of the project we expect to have a cohort of >15,000 genomes and >8,000 families. The primary challenge of genome analysis is that the capacity of WGS to discover genetic variants substantially exceeds our ability to interpret their functional and clinical impact. We are uniquely placed to make use of the opportunities provided by the 100K project to investigate neurodegenerative disorders, due to: a) the genome sequencing of a large number of neurology probands and family members, b) the unique nature of the NHS healthcare system that allows us to track patients and access large amounts of clinical information associated with each sample that will be crucial for variant interpretation, c) the collection of biosamples available from probands and relatives that will allow downstream biological analysis, and d) the 100K NHS consent to go back to families up to four times per year for further research needs and with the majority of neurology families based at our institutions this will be important for deeper phenotypes and further samples.As a team, we already have an impressive track-record in neurogenetics. We have used WGS data to identify and characterise a wide range of mutation types and disease genes, including point mutations, genomic duplications and deletions, novel de-novo and mosaic mutations, newly identified expressed non-coding regions that we have re-annotated and recently an unpublished novel repeat expansion that causes ataxia (see preliminary data in the case for support).We will apply an integrated analytical approach in this proposal, by investigating and identifying the genomic abnormalities in the undiagnosed neurological disorders in the 100K, focusing on inherited neurodegenerative and combining this with the clinical data collected. We will identify a large number of potentially pathogenic variants and optimise variant annotation and prioritisation using brain transcriptome data. We will use RNA sequencing to further increase the diagnostic yield, and the availability of additional sequenced disease cohorts through our research and collaborations will increase our ability to validate the pathogenicity of new disease genes and expand the disease phenotypes. Using this approach, we will identify new genes and common mechanisms responsible for specific phenotypes that have an impact across the spectrum of Mendelian and non-familial neurodegenerative disorders. This will also allow us to re-definite of the classification of neurodegenerative diseases based on the use of WGS and the advanced understanding of the molecular mechanisms, as opposed to the traditional 'major-phenotype' based approach currently used to date. This proposal is timely, with complete release of the entire 100K WGS dataset on 31/12/2018. Our approach will increase our capacity to diagnose new neurological disorders, whist also defining new mechanisms and pathways of diseases. Inherited and aggressive disorders are likely to involve defects in key cellular pathways, involving mechanisms relevant many forms of common neurodegenerative disorders that will underpin the development of treatments for currently incurable disorders.