To build on NHS research collaborations to enhance the clinical interpretation and validation of whole genome sequencing.
To identify new disease genes, genetic risks and modifying factors for disease. This will enable comprehensive NHS diagnostic testing, prediction of disease and disease severity.
To identify and investigate the actions of genetic factors involved in neurological disease – in order to advance understanding of the underlying cause of disease.
To collaborate widely with other GeCIP domains and form partnerships with industry to convert genetic findings into treatments.
Train the next generation NHS scientists, analysts and clinicians in genomic medicine.
Below are the current subdomains for this domain. You can find the full details of the research proposed by this domain in the Neurology GeCIP detailed research plan.
|SUBDOMAIN||SUBDOMAIN LEAD/S||RESEARCH DESCRIPTION|
|Ataxia, chorea and other hyperkinetic movement disorders||Andrea Nemeth |
|Ataxia, chorea and other hyperkinetic movement disorders are frequently seen in the neurology clinic but fall within the ‘rare-disease’ category with an overall frequency of around 5-10/100,000. Ataxia is genetically defined in around 60% of patients and Huntington’s disease (HD) is diagnosed in around 80% of the choreiform conditions but nearly all are currently untreatable. Teams within GeCIP have contributed to the increase in molecular diagnosis in this group but many still do not have a genetic diagnosis. There are excellent UK and European collaborations for gene identification, and validation of potential pathogenic variants as well as novel assays for investigating the pathogenicity, understanding disease mechanisms and carrying out novel drug screening.|
|Dementia and Motor Neuron Disease (MND)||James Rowe |
|One in six people aged 80 and over have dementia, while early onset dementias (<65 years old) affect around 40,000 people in the UK. Alzheimer’s disease (AD) and frontotemporal dementia (FTD) are the commonest causes of dementia and thought to explain 50–70% of all cases. After age, a family history of AD/FTD is the most important risk factor and studies of dizygotic and monozygotic twin pairs have revealed heritability estimates of between 60% and 80%. Our greatest understanding of AD, FTD and other causes of dementia has come from the identification of inherited disease genes. In AD, three autosomal dominant genes; APP, PSEN1, and PSEN2 account for around 65% of early onset disease.
Important risk factors for late onset AD also exist, such as ApoE4. In FTD 40% of patients have a family history and the important genes identified include MAPT, GRN and C9ORF72. Overall, mutations in GRN, MAPT and C9ORF72 together account for 17% of FTD cases (mutations in VCP and CHMP2B are rare, each explaining less than 1% of the familial FTD).
Motor neurone disease (MND, also called a myotrophic lateral sclerosis, ALS) is a relentlessly progressive neurodegenerative disorder with just three years average survival. Overlap in the pathology and genetics of MND and FTD is so great that they are now considered phenotypic variants of a common disease spectrum.
|Developing a streamlined system to interpret and report genome sequencing results in the diagnostic laboratory||James Polke||An important part of the 100,000 genomes project is the implementation and long-term sustainability of genome sequencing as an NHS diagnostic test for the UK population. Transferring the experience, knowledge and techniques gained from the 100,000 genomes project into the diagnostic laboratory setting will be essential in establishing this important test into routine NHS diagnostic test.
Several of the larger diagnostic genetics laboratories around the UK have already implemented next generation sequencing gene panels into practice but the use of genome sequencing will be the ultimate genetic test. There will be a number of important tasks to perfect in the development of stringent diagnostic genome sequencing that range from data handling and long term storage of results, through to genomic coverage and variant interpretation. In addition, in the first instance genome sequencing will likely be combined with Sanger sequencing but as laboratories become more experienced and confident the use of Sanger sequencing will likely become redundant.
|Genome sequencing in very rare inherited neurological disorders: Identifying overlapping common pathological pathways||Tom Warner|
|Rare inherited neurological disorders such as hereditary spastic paraplegia (HSP), leukodystrophy, moyamoya disease and idiopathic basal ganglia calcification are separately rare with individual disease incidences of around 1-2 per 100,000 but altogether they account for a significant proportion of neurological disease. The molecular diagnostic rate varies between these disorders, in HSP around 60-70% of the genes have been identified but in disorders such as moyamoya disease the number of disease genes are few. No specific treatments are available in these conditions and identifying disease genes and pathways in these groups will not only allow an accurate diagnosis but also reveal important information on overlapping pathways in commoner neurological disorders.|
|Mitochondrial Disorders||Patrick Chinnery||Mitochondrial disorders have emerged as one of the largest groups of inherited neurometabolic disease. Epidemiological studies indicate that they affect approximately 1:5,000 of the population.(1) A molecular diagnosis is only possible in approximately half of these families. A proportion have mutations of mitochondrial DNA (mtDNA) responsible for their disorder. The remainder have a presumed nuclear genetic defect which can be autosomal dominant, autosomal recessive or X-linked. (2)
Whole exome studies have had a major impact on the molecular diagnosis of mitochondrial disorders (e.g. (3)). This has led to the identification of a wide array of new genetic causes for defects of the mitochondrial respiratory chain, revealing new mechanisms potentially amenable to treatment. However, conventional exome approaches have only identified molecular basis in approximately 60% of families, leaving a large minority without a genetic diagnosis.
|Movement Disorders||Huw Morris|
|Movement Disorders encompass a wide range of disorders from the common neurodegenerative disorder Parkinson’s disease (prevalence 140/100,000) to much rare childhood onset dystonias and neurometabolic conditions (prevalence <10/100,000). Within the Movement Disorders sub- domain, we will focus on: i.) familial and early onset Parkinson’s disease (PD); ii.) early-onset and familial dystonia and iii.) complex parkinsonism (including pallido-pyramidal syndromes).
PD: PD is heterogeneous spanning both “sporadic” late onset disease and early onset Mendelian versions of PD. From the 1990s forward autosomal recessive genes for early onset PD (parkin, PINK1 and DJ1) have been identified which have a common effect in regulating mitochondrial function (4).
Dystonia: An increasing number of genes for early onset dystonia/hyperkinetic movement disorders have been identified in individuals without a family history of disease, which includes both gene variants of reduced penetrance and de novo mutations.
Complex parkinsonism: Complex parkinsonism includes a series of “overlap” syndromes in which parkinsonism occurs with dementia, an eye movement disorder and/or a neuro-metabolic condition in some cases including neurodegeneration with brain iron deposition (NBIA). Most genes responsible for early onset complex parkinsonism are autosomal recessive.
Importantly, in each of these disease areas there are a substantial number of unexplained cases.
|Neuromuscular Disorders||Mike Hanna |
|Neuromuscular diseases (NMD) are untreatable muscle-wasting conditions that affect >100,000 people in the UK. They are genetic or acquired, span neonatal life to late age, and cause premature death or lifelong disability. For example, Duchenne dystrophy patients die in young adult life whereas most patients with inherited neuropathies have a normal lifespan but with significant morbidity. Disruption of neuromuscular systems biology underpins NMDs. The molecular diagnostic rate varies between these disorders, in proximal myopathy around 80% of the genes have been identified but in disorders such as Charcot Marie Tooth (CMT) disease type 2 only around 50% of patients have a genetic diagnosis.|
|Paroxysmal Neurological Disorders||Arjune Sen|
|Paroxysmal neurological conditions include epilepsy, episodic movement disorders, headache and episodic pain. These are some of the commonest neurological conditions seen but in general they are poorly understood and underdiagnosed. They affect people across their lifespan meaning that the socioeconomic impact of these diseases is vast. There is also sudden unexpected death in epilepsy (SUDEP) where there is growing evidence of a genetic basis for SUDEP, with contributions that may be both monogenic (5) and distributed across the genome (6) –WGS would be an ideal way to determine individual risk of SUDEP and genetic cause in one test. The treatment of these conditions is limited and many patients are resistant to multiple forms of medication and some conditions such as cluster headache are extremely difficult to treat.|
|Training subdomain–Neurological disorders||Huw Morris||A key aim of the 100K Genome project is to use genomic medicine to improve health outcomes across the UK, within the NHS. To do this we will need to train both current practicing physicians and professions allied to medicine (PAM), and the next generation of physicians and clinical specialists to ensure that they are able to interpret and explain individual patient level genomic data, and to use the results of the 100K-genome project to develop new and improved treatment. This training programme will need to include specialists from clinical genetics and adult and paediatric neurology. The training sub-domain of neurological disorders is clearly of central importance to the overall project.
Traditionally, genetics teaching has focussed on modes of inheritance and classical genetic diseases. To equip and prepare our current and future clinicians we need to provide training in the new areas that will be imminently relevant to clinical practice including for example: the consent process for clinical and research-based genetic testing, the correct procedures in relation to incidental genetic findings, the definition of pathogenic and non-pathogenic variants, de novo pathogenic mutations, age-dependant variation in penetrance, genome wide association study variants, genomic risk profiles and personalised medicine. In addition, we propose that training for all clinicians in genomics should include some familiarity with areas that lie firmly within clinical genetics such as predictive, pre-natal and pre-implantation genetic diagnosis.
|Transforming the diagnosis and understanding of neurological disorders through the creation of resources for variant prioritisation||Mina Ryten|
|Over the past 5 years there has been a massive growth in genetic testing both in terms of the scope and the numbers of individuals offered genetic testing. This “genomic” revolution has had an immense impact on the diagnosis and understanding of neurological conditions. There is good reason to believe that whole genome sequencing (WGS) will not only increase discovery of pathogenic variants and genes, but will have a disproportionate impact on the understanding of neurological disorders as compared to other disease areas.
Realising the potential of WGS for neurology will be challenging. The reliable identification of genuine disease-associated genetic variants, particularly in genomic regions currently annotated as intergenic or intronic, from amongst the broader background of variants present in all human genomes that are rare, but not actually pathogenic is a major concern. Addressing this issue requires a systematic approach to variant prioritisation and assignment of pathogenicity based on multiple different data sources.
|Understanding disease and deep phenotyping||Volker Straub||Genetic neurological diseases are a real challenge for our society. Despite the fact that they are individually considered as rare, together they affect many, bringing a huge burden for patients and their families as well as to the healthcare system. Many of these conditions lead to premature death or chronic debilitation. They are currently incurable and because of their underlying genetic causes are associated with risk of recurrence for the families affected. Understanding and better describing neurological phenotypes is key to identifying patients and providing highly stratified cohorts in readiness for clinical trials.
Clinicians and scientists frequently have an expertise in many different genetic neurological conditions, and are involved in common research networks, databases, registries, and multicentre clinical trials. Extensive patient DNA and tissue collections are available, accelerating research and facilitating translational steps such as developing biomarkers and treatment concepts. This will be exploited within this GeCIP and the established networks will be used to define core phenotypic data sets to be collected across the diseases included in this GeCIP. In consultation with other disease-specific GeCIPs, we will ensure that areas of clinical overlap will be described in a harmonised way.
Linking phenotypic and long-term outcomes data with whole genome sequences will generate a uniquely rich and longitudinal dataset which will be invaluable to advancing understanding of these conditions.
1) Gorman, G. S. Et al. Prevalence of nuclear and mitochondrial DNA mutations related to adult mitochondrial disease. Ann Neurol 77, 753-9(2015). (mtD)
2) Stewart, J. B. & Chinnery, P. F. The dynamics of mitochondrial DNA heteroplasmy: implications for human health and disease. Nature Reviews Genetics (2015). (mtD)
3) Taylor, R. W. Et al. Use of whole-exome sequencing to determine the genetic basis of multiple mitochondrial respiratory chain complex deficiencies. JAMA 312, 68-77 (2014). (mtD)
4) Cookson MR, Bandmann O. Parkinson’s disease: insights from pathways. Hum Mol Genet. 2010 May;19(1):21–7. (MD)
5) Bagnall R D et al. Exome-based analysis of cardiac arrhythmia, respiratory control and epilepsy genes in sudden unexpected death in epilepsy. Ann Neurol. 2015 Dec 24. doi: 10.1002/ana.24596. (PNC)
6) Leu C et al. Genome-wide Polygenic Burden of Rare Deleterious Variants in Sudden Unexpected Death in Epilepsy. EBioMedicine. 2015 Jul10;2(9):1063-70. (PNC)