Using transcriptomics to transform the diagnosis and understanding of inherited adult neurological disorders

We all inherit an instruction manual for making the human body and this is encoded in our DNA. Unfortunately, spelling mistakes or mutations in our DNA can increase our risk or even directly cause certain disorders including disorders, which mainly affect the brain and nervous system in adults. Recognising the mutations that cause these disease can be difficult. This is because we all carry many mutations within our DNA most of which are probably harmless and because the brain is a very complicated organ. However, it is important that doctors and researchers find ways of assessing the importance of specific mutations so that we can improve the way in which we diagnose people with rare inherited neurological diseases and so that we can find new ways to treat these conditions. This is particularly important now that more people are being offered testing to look for mutations in their DNA and that technological advances mean that we can potentially test all of a patient's DNA (not just a small part).

One way to try and decide whether mutations in the DNA are contributing to neurological diseases is by understanding more about which parts of the DNA are expressed in the human brain and the impact that changes in the DNA have on the expression of particular genes (the basic building blocks of the DNA) in the brain. In order to check this, researchers need to make measurements about the genetic variation an individual carries and link this information to the genes they express in their brain cells. Although making these types of measurements in the brain is very difficult, it is possible and this is the aim of this project. One of the challenges is accurately measuring the amount of each of the genes expressed in specific parts of the brain and even in the specific types of cells in the brain. I will try and overcome this challenge in two ways. Firstly, I will study gene expression data from 12 different regions of the human brain and central nervous system taken from people who have donated their brain to a brain bank. Secondly, I will study cell types found in human brain that have been made in culture. These cells start as a patient's skin cells, but are then converted into induced pluripotent stem cells, a very special kind of cell that can be used to make lots of different types of cells in the human body including brain cells.

This project also uses a new technology for measuring all the genes expressed in a single cell type or tissue sample. This technology is called "RNA-seq" or "whole transcriptome sequencing" and it allows researchers to measure all kinds of genes at the same time. It also allows us to measure the relative amounts of alternative versions of the same gene, and to measure these quantities in such a way that the influence of genetic risk factors can be more sensitively detected by directly comparing the relative amounts in individuals who happen to have both a "good" and a "bad" copy of a given genetic variant. In order to make more sensitive measurements about some types of RNA I will also be making measurements from two main parts of the cell, called the nucleus and cytoplasm.

By making all these measurements about the way genes are expressed in the human brain and brain cells, I will create a very detailed map of gene expression in the human brain together with a map of how this expression is controlled. Most importantly, I will work with other doctors and researcher and use the detailed map to try and help reach a diagnosis in specific patients. In this way, I will find out whether having detailed information on the expression and regulation of genes in the human brain really does help us to better diagnose and understand inherited brain diseases.

The aim of this study is to determine the effect of genetic factors on whole transcriptome expression in the human central nervous system and in brain-relevant cell types with the primary aim of transforming diagnostics for adult inherited neurological disorders. This project is inspired by the growth in whole genome sequencing in patients, which is likely to drive the discovery of an increasing number of potentially pathogenic variants within non-coding regions of the genome. Prioritising such variants for further analysis and understanding the molecular processes and regional/cellular site of action is key to ensuring diagnostic accuracy and driving further research. I aim to address both these important issues. Using control post-mortem human tissue from 12 regions of the human central nervous system, and through analysis of paired nuclear and cytoplasmic RNAseq data, I will define the transcribed portion of the human genome in adult brain. This data will also be analysed using allele-specific expression (ASE) analysis to identify genetic loci that regulate the expression of specific gene transcripts within specific tissues. A similar approach will be taken to the analysis of RNA sequencing data generated from brain-relevant cell-types originating from human induced pluripotent stem cells. This data will be used to explore cell and state-specific regulation of gene expression in brain-relevant cell types. Through collaboration with the neurology domain of the Genomics England Clinical Interpretation Partnership, I hope to test the value of this approach in real clinical scenarios and in some cases through additional RNA sequencing of patient samples. All the data generated by this project will be publicly released as both raw data files for re-analysis and processed information suitable for non-expert users. Thus, I will generate novel disease-relevant findings and provide the neuroscience community with a world-class resource.

The goal of this work is to use transcriptomics to transform the diagnostic process and improve the understanding of inherited adult neurological disorders. Reaching this goal will require many intermediate steps and I describe who I envisage using the research findings and how this data will help them.

Clinicians and clinical scientists: This study will provide a detailed map of the transcribed portion of the human genome and the underlying regulatory architecture in human brain. This information will inform decisions about the prioritisation of rare variants for further investigation following whole genome sequencing. This will be facilitated through the neurology domain of the Genomics England Clinical Interpretation Partnership (GECIP). Given that the 100,000 Genomes Project is also committed to the collection of "omics" samples, including blood samples suitable for transcriptomic analysis, in some cases such samples may be requested and analysed.

Researchers interested in the follow up of genetic variant data: This study was designed to improve our understanding of the molecular mode of action and cellular location in which genetic variants for adult neurological disorders operate. Therefore, users of the data would include international consortia for neurological diseases, such as the International Parkinson's Disease Genetics Consortium amongst others. Since I will be publicly releasing all findings through the UK Brain Expression Consortium's web portal (www.braineac.org), I envisage other less specialist researchers also accessing the data. This could include drug companies interested in following up genetic findings for clinical trial design or biomarker development.

Researchers interested in the creation and use of in vitro model systems: The generation of region-specific and cell-specific whole transcriptome sequencing data produced in this project will be a baseline for the detailed molecular assessment of stem cell-based disease models. I will work collaboratively to identify the strengths and weaknesses of existing cell models and work to improve the accuracy of these systems. Thus, I will contribute to the development of new research tools for use by the neuroscience research community.

Basic neurobiologists: The large gene expression data sets I am producing will provide insights into other aspects of basic neurobiology. Sequencing of paired nuclear and cytoplasmic RNA will provide a unique resource for the analysis of pre-mRNA processing. This may provide the basic information required to develop novel approaches to manipulating these processes to "salvage" mutations through facilitating exon-skipping or use of alternative promoters. In the longer term, I believe that this data could facilitate research into novel therapeutic approaches.

Bioinformaticians & statistical geneticists: The paired exome and RNA sequencing data will be used by statistical genetics and bioinformatics wishing to test and develop new statistical and analytical methods. In particular, the existence of paired nuclear and cytoplasmic RNA sequencing data will allow researchers to objectively test and improve methods for transcript calling. Therefore, I will directly contribute to one of the MRC's stated aims, the training of more researchers and clinicians in bioinformatics.

Charities & patient groups: The rapid discovery of genetic variants for inherited neurological disorders represents the most significant advance in the understanding of these diseases in the last 10 years. Therefore, they are hugely important to patients and carers desperately seeking progress in the diagnosis and treatment of their diseases. From my experience of contact with patients and charities, it is clear that engaging with patients and communicating the findings generated from research is vital to maintain hope and improve the uptake of clinical trials.