Deciphering the effects of genetic variability in regulatory T cells - links with autoimmunity

Lead Research Organisation: The Wellcome Trust Sanger Institute
Department Name: Computational Genomics

Abstract

The role of the immune system is to defend an individual from infectious agents and clear the body from harmful own elements, such as e.g. cancerous cells. This is orchestrated by a number of specialised immune cells that recognise and eliminate potentially dangerous components. At the same time, the immune system undergoes careful negative control that restricts the immune response to the necessary minimum. This is carried out by regulatory T cells (Tregs). However, under certain conditions, the immune cells can react against individual self tissues as if they were harmful factors. If such an immune response is not restrained, it can lead to the development of chronic inflammation and pathogenic conditions known as autoimmune diseases.

Autoimmune diseases can be debilitating, difficult to diagnose and frequent - they affect one in ten individuals in Western countries. The exact origin of autoimmune diseases is unknown, although they are thought to result from a combination of environmental and genetic factors. To date, hundreds of studies have linked thousands of genetic variants with increased risk of developing immune diseases. However, establishing the functional effects of these genetic variants remains challenging.

The role of genetic variants associated to autoimmune diseases has been linked with modulating function of Tregs. In this project, I propose to use large scale genomic and immunologic assays to characterise the activity of Tregs from healthy individuals and correlate it with genetic variants. Genomic assays will provide the measurement of gene activity, while the immune assays will provide information on cell activity. I will use data from cells in resting and stimulated states - the later is used to mimic physiologically occurring immune response.

My goal in this project will be to develop new computational tools and methods that will pioneer an integrative framework to combine these data in a meaningful way. Ultimately, I want to identify what are the exact causal molecular mechanisms through which genetic variants predispose to autoimmune diseases.

The findings of this project will have benefits on both scientific and social levels. In a direct way, our results will help to understand the mechanisms that cause the failures in the immune system that lead to the onset and progression of autoimmunity. This information potentially can be of high impact for the patients as it will identify new therapeutic targets.

Technical Summary

Aims: The majority of the causal variants underlying associations to complex traits remain unknown. This proposal aims to define the causal variants at loci associated with autoimmune diseases, by studying the effects of of associated variants on CD4+ regulatory T cells (Tregs).

Objectives: Specifically, I will 1) construct a catalogue of chromatin and gene activity in Tregs from 100 individuals, 2) functionally prioritise putative causal variants based on their effects on gene regulatory features, as well as 3) gene and cytokine expression levels and 4) assess if the observed effects are specific cellular states, resting or stimulated.

Methodology: Dr Trynka's group is generating functional genomic data from Tregs from 100 healthy blood donors. The assays include: 1) genome wide genotyping, 2) characterising active promoters by ChIP-seq for H3K4me3 histone modification , 3) mapping open chromatin regions using ATAC-seq, and 4) quantifying gene expression with RNA-seq. Assays 2-4 include both resting and stimulated Tregs. Using these datasets I will identify genetic variants that co-localise with H3K4me3 and ATAC features and test for correlation between alleles and the number of mapped sequence reads. Variants with allele-specific effects on histone modification levels or chromatin accessibility will comprise a pool of prioritised causal variants. I will further correlate these alleles with gene expression levels and assess the genetic effects on cytokine levels. Finally, if a subset of nominated causal alleles point to disrupted transcription factor binding (TF), I will perform functional validation using TF-specific ChIP-seq.

Scientific and medical opportunities: We will gain insights into the causal molecular mechanisms underlying the immune disease loci that may lead to identification of novel drug targets and disease biomarkers. Finally, the framework proposed here can be easily adapted to other cell types and complex traits.

Planned Impact

Although individually ADs may be perceived as rare diseases, collectively autoimmune disorders affect 5-10% of the population in Western countries. These disorders are often chronic and disabling, causing great patient suffering. Furthermore, autoimmune disorders often co-occur and aggregate in families, increasing the familial burden of the affected individuals. Patient care and treatment is expensive and typically life-long, posing high costs for the public health system. The translation of our findings to patient care is a long term but essential aim of the present project. Often diagnosis of ADs is difficult and can delay treatment, which normally consists of a combination of biologic agents and conventional disease-modifying drugs, such as methotrexate. These treatments affect pleiotropic molecules and pathways and often result in drug-induced intolerances and discontinuation of the treatment becomes necessary. The proposed study will deliver a better understanding of biology of regulatory T cells (Tregs) and the identification of either the target genes or the transcription factors whose binding is altered by the genetic variants associated to autoimmune disease. This may lead to the selection of novel relevant molecules or pathways that could be used as potential therapeutic targets. Importantly, rather than acting generically they could directly impact pathways specific to Tregs. As a consequence, these results may provide both improved specificity of treatment and increased patient tolerance. Therefore, great benefits for patient treatment and prognosis may arise from these initiatives, saving human and economic costs for the society.

Because of the cross-disciplinary nature of our study, bridging genomics with immunology, I expect that our results will impact a diverse scientific community and provide a valuable resource to researchers in the fields of immunology, cellular biology, and those working on autoimmune diseases with strong links to Tregs not covered in our analysis. For instance, publically available genomic data from human Tregs is scarce and our project will fill this gap by providing a comprehensive catalogue of gene regulatory regions and key pathways active in stimulated and resting Tregs. Similarly, the analytical approaches that I will develop here will be generally applicable to a wider range of cell types, conditions, and diseases, amplifying the scope and relevance of our investigation to other fields.
 
Title ATAC-seq processing pipeline 
Description I have developed a robust framework including: quality control, processing, filtering, mapping and peak calling of the sequence reads from Assay for Transposase-Accessible Chromatin (ATAC-seq). 
Type Of Material Data handling & control 
Year Produced 2017 
Provided To Others? No  
Impact This pipeline has been tested in our first 60 ATAC-seq samples showing great reproducibility. The analysis of ATAC-seq data is a developing field with no clear gold-standard procedures yet. Therefore, the community may benefit from establishing consistent pipelines with clear quality controls and checkpoints as the one described above. Moreover, I have used our ATAC-seq outcome in a recently published allele-specific quantitation framework to define chromatin accessibility quantitative trait loci (caQTLs) in CD4+ T regulatory cells with promising results in our pilot cohort. 2018 Update -) This pipeline has been successfully applied to the complete set of ATAC-seq samples. I performed caQTL analysis including the entire recruited cohort. The processed sequencing data have been including in a collaboration to study transcription factor activity in Tregs. 2019 Update: The pipeline is ready to be shared with the community, as part of the manuscript publication resources. 
 
Title ChIPmentation processing pipeline 
Description In collaboration with other members of the team (Dafni Glinos, PhD student), we have developed a robust pipeline for ChIPmentation data filtering and quality control. 
Type Of Material Data handling & control 
Year Produced 2018 
Provided To Others? No  
Impact This pipeline has been tested and adapted to pilot data of 5 ChIPmentation (ChM) assays comprising H3K27ac and H3K4me3 histone modifications. The output showed with consistent and reproducible outputs. The method is ready to process the remaining samples, which will be available in a month. The output of this pipeline is ready to use with gold standard quantitative trait loci (QTLs) analysis software. 2019 Update: The pipeline has been used to process the 200 regulatory T cell samples included in the project and is ready to be shared with the community, as part of the manuscript publication resources. 
 
Title Chromatin Element Enrichment Ranking by Specificity (CHEERS) Method 
Description To assess the immune disease enrichment across different but closely related cell states, I contributed to a project, leaded by my colleague Dr Blagoje Soskic and my group leader Dr Gosia Trynka, the developed a new SNP enrichment method, CHEERS (Chromatin Element Enrichment Ranking by Specificity). The method combines SNP-peak overlap with chromatin modification peak properties as reflected by quantitative changes in read counts within peaks, corresponding to variable levels of H3K27ac or chromatin accessibility. 
Type Of Material Computer model/algorithm 
Year Produced 2019 
Provided To Others? Yes  
Impact We were able to discriminate differential enrichment between, for example, inflammatory bowel disease variants that are enriched in chromatin regions active in Th1 cells, while asthma variants overlap regions active in Th2 cells. In the case of macrophages, we observed that Alzheimer's disease variants are enriched in several states. Our results represent the first in-depth analysis of immune disease variants across a comprehensive panel of activation states of T cells and macrophages. Moreover, the manuscript is currently under review in Nature Genetics. 
URL http://dx.doi.org/10.1101/566810
 
Title RNA-seq processing pipeline 
Description In collaboration with other members of the team (Dafni Glinos, PhD student), we have developed a robust pipeline for RNA-seq filtering and quality control. 
Type Of Material Data handling & control 
Year Produced 2017 
Provided To Others? No  
Impact This pipeline has been tested and adapted to our data in the first 60 RNA-seq samples showing great reproducibility. It is ready for the processing of the remaining samples in due course. Moreover, we used available RNA-seq analysis software packages to determine differentially expressed genes and combine this information with genotyping data to identify expression quantitative trait loci (eQTLs) in these samples. 2018 Update -) This pipeline has been successfully applied to the complete set of RNA-seq samples. We have also performed eQTL analysis including the entire recruited cohort. 2019 Update: The pipeline has been used to process 24 additional T cell samples included in the project and is ready to be shared with the community, as part of the manuscript publication resources. 
 
Title T regulatory cells "omics" resource 
Description We have isolated T regulatory cells (Tregs) from blood samples of 136 healthy donors. The sequencing outputs for ATAC-seq and RNA-seq and the genotyping information for half of these donors have already been processed and the remaining sequencing libraries have already been included in the sequencing pipeline at the Sanger Institute. Current group efforts include optimisation of protocols for the ChIP-seq experiments for active promoter-associated histone marks and samples will be submitted for sequencing by June 2017. For a small subset of individuals (12 donors), ATAC-seq and RNA-seq experiments were performed both after activation of the Tregs with PMA and ionomycin and after culture in resting state. In addition, imputed genome-wide SNP information was generated. This resource will be accessible to the scientific community according to the open access policy of the Sanger Institute, at the end of the study. 2018 Update -) Sequencing outputs for ATAC-seq, RNA-seq and genotyping for the entire cohort underwent quality control and processing using the developed pipelines. Moreover, quantitative trait loci (QTL) analysis has been performed for both the transcriptome (eQTLs) and the chromatin accessibility (caQTLs) datasets. On the ChIP-seq front, we have decided to use ChIPmentation (ChM), which is a fast, robust and low-input ChIP-seq method variation for histone modifications and transcription factors. I analyzed the performance of the method in our samples with remarkable results. Then, I identified the most informative histone marks considering overlap with genetic regions associated to immune-related diseases in GWAS. Consequently, histone modifications related to active promoters, H3K4me3, and active enhancers, H3K27ac, were assayed using the above method. The pilot sequencing outputs and the developed pipeline have shown reliable and promising results. Moreover, I will receive the complete ChM sequencing results obtained in the Sanger sequencing facilities in a month. After quality control and processing, QTL analysis will be also carried out in the histone mark datasets and they will be added to the resource at the end of the study. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? No  
Impact These data base will be an unprecedented resource for a very scarce and uncharacterized T cell subtype. I have already started addressing the existence of cell-specific and activation specific differentially expressed genes, differentially accessible chromatin regions, expression quantitative trait loci (eQTLs) and chromatin accessibility QTLs (caQTLs) in the pilot cohort. Furthermore, I have also observed that different eQTLs or caQTLs overlap with or are linked to immune-related susceptibility loci. The analysis of the transposase accessible chromatin regions in the T regulatory cell (Treg) population has shown a significant enrichment in immune-related transcription factor motifs. From the analysis of the available data, I am confident to conclude that there is evidence supporting that the collected data provides valuable insights into Treg biology and the role of genetic variation in the control of the Treg function. Remarkably, Tregs have a very relevant role in the control of the immune system and this knowledge will arouse great interest not only for the scientific community but also for the medical research community. Dissemination of preliminary results at conferences has resulted in great enthusiasm from the immunogenomic community. 2018 Update -) The complete set of RNA-seq and ATAC-seq data have been processed and analysed in the past year. We have defined 40,257 high confidence chromatin accessible regions and captured the expression of 13,275 genes in regulatory T cells. We have identified the effects of thousands of eQTLs in gene expression. Interestingly, approximately 15% of them seem to be cell specific effects and we have found significant colocalization with GWAS SNPs associated to different immune-related diseases, especially for inflammatory bowel disease (IBD), rheumatoid arthritis and type-1 diabetes. We have also found more than a thousand chromatin accessible regions under genetic control (caQTLs). A majority of the caQTLs can be linked to eQTL effects in nearby genes. The analysis of histone modifications is still ongoing. Our results support the value of our cohort in the analysis of the function of genetic variants associated to autoimmune diseases and their link with immune-mediated disease susceptibility. 2019 Update -) Colocalization of GWAS signals with Treg QTLs linked immune disease alleles to effects on 80 genes. We observed the highest number of GWAS variants to colocalize with active enhancer and promoter QTLs marked by H3K27ac, implicating that many of the effects will likely manifest in cell state specific manner. The disease colocalizations point towards dysregulation of Treg specific pathways, including Treg response to stimulation via CD28 and IL-2 signalling modulated by STAT5A signalling. Finally, by integrating disease GWAS signals that colocalized with Treg QTLs with Open Targets platform we identified 14 targets currently bound by drugs and 61 additional targets with promising drug tractability. The resource will be available when the manuscript, currently being assesed by the co-authors, is published. 
 
Title The Treg genotype, ATAC-seq, ChIP-seq and RNA-seq data used in this project have been deposited in EGA (devweb) 
Description We have deposited the datasets included in this project in the EGA, the data will remain under embargo until the main manuscript is published but the data are already accessible for reviewers. This dataset maps gene expression regulation in human primary regulatory CD4 T cells (Tregs). It includes whole genome sequence data for ChM-seq (118 H3K4me3, 118 H3K27ac and 6 inputs), ATAC-seq (114 samples) and whole transcriptome (141 samples). All individuals were genotyped (130 samples) using coreExome Illumina SNP chip array. The final quality filtered set included 123 individuals with RNA-seq data, 73 with ATAC-seq, 91 with H3K27ac ChM-seq and 88 with H3K4me3 ChM-seq data. A total of 62 individuals had QCed data for all the assays. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? No  
Impact When the manuscript is published the data will be accessible for the community, meanwhile it will be available upon request (EGA study id: EGAS00001003516). 
 
Description Department of Health Sciences, University of Leicester; National Institute for Health Research, Leicester Respiratory Biomedical Research Unit, Glenfield Hospital, Leicester- Louise V Wain, Martin D Tobin and collaborators 
Organisation University of Leicester
Country United Kingdom 
Sector Academic/University 
PI Contribution In this collaboration, I contributed to the data analysis of a genome-wide association study for lung function and chronic obstructive pulmonary disease applying tests for cell/tissue-specific enrichment of associated variants with histone marks. The statistical framework of the enrichment analysis and the knowledge on epigenetic marks were new to me at the moment of initiating my MRC fellowship. By the end of this collaboration, I was able to confidently implement this approach and interpret the results, which lead to a co-authorship of a manuscript published in Nature Genetics, where I contributed to the writing of the corresponding results and discussion paragraphs. Additionally, this collaboration provided me with a knowledge in a new, non-immune phenotype.
Collaborator Contribution The study design and the GWAS genotyping data and core analyses were provided by the collaborators at the University of Leicester. The writing of the manuscript was led by the group at University of Leicester.
Impact This collaboration resulted in the publication of a manuscript: Nat Genet. 2017; 49: 416-425. doi: 10.1038/ng.3787. Genome-wide association analyses for lung function and chronic obstructive pulmonary disease identify new loci and potential druggable targets. Wain LV, Shrine N, Artigas MS, Erzurumluoglu AM, Noyvert B, Bossini-Castillo L, Obeidat M, Henry AP, Portelli MA, Hall RJ, Billington CK, Rimington TL, Fenech AG, John C, Blake T, Jackson VE, Allen RJ, Prins BP; Understanding Society Scientific Group, Campbell A, Porteous DJ, Jarvelin MR, Wielscher M, James AL, Hui J, Wareham NJ, Zhao JH, Wilson JF, Joshi PK, Stubbe B, Rawal R, Schulz H, Imboden M, Probst-Hensch NM, Karrasch S, Gieger C, Deary IJ, Harris SE, Marten J, Rudan I, Enroth S, Gyllensten U, Kerr SM, Polasek O, Kähönen M, Surakka I, Vitart V, Hayward C, Lehtimäki T, Raitakari OT, Evans DM, Henderson AJ, Pennell CE, Wang CA, Sly PD, Wan ES, Busch R, Hobbs BD, Litonjua AA, Sparrow DW, Gulsvik A, Bakke PS, Crapo JD, Beaty TH, Hansel NN, Mathias RA, Ruczinski I, Barnes KC, Bossé Y, Joubert P, van den Berge M, Brandsma CA, Paré PD, Sin DD, Nickle DC, Hao K, Gottesman O, Dewey FE, Bruse SE, Carey DJ, Kirchner HL; Geisinger-Regeneron DiscovEHR Collaboration, Jonsson S, Thorleifsson G, Jonsdottir I, Gislason T, Stefansson K, Schurmann C, Nadkarni G, Bottinger EP, Loos RJ, Walters RG, Chen Z, Millwood IY, Vaucher J, Kurmi OP, Li L, Hansell AL, Brightling C, Zeggini E, Cho MH, Silverman EK, Sayers I, Trynka G, Morris AP, Strachan DP, Hall IP, Tobin MD. This collaboration was multidisciplinary since it involved several clinical departments (respiratory, pulmonary, cardiology, pathology, epidemiology, etc.) based on hospitals worldwide (UK, Europe, America and Australia), immunology groups, pharmaceutical companies (Merck Research Laboratories, Regeneron Pharmaceuticals) and also medical and basic genetics research groups.
Start Year 2016
 
Description Enhacer KO in Tregs - Dr Roychoudhuri (Babraham Institute) 
Organisation Babraham Institute
Country United Kingdom 
Sector Academic/University 
PI Contribution We identified a Treg specific LRRC32 (encoding Glycoprotein A Repetitions Predominant, GARP) expression quantitative trait locus (eQTL) in our dataset. We also observed that there is colocalization of this signal with GWAS associations for IBD and asthma. Finally, we have also mapped this signal to a Treg enhancer marked by H3K27ac in our preliminary data. I have analyzed in depth the linkage disequilibrium patterns, genetic variants, transcription factor binding sites and chromatin configuration of this region. I am also directly involved in the writing of a manuscript reporting the results of this project.
Collaborator Contribution The Roychoudhuri team are experts in using a syntenic alignment approach and CRISPR/Cas9-based mutagenesis to discover the role of enhancer regions in T cell biology. Interestingly, they defined a region of mouse chromosome 7 homologous to a human enhancer region required for Treg-specific expression of GARP. Treg-specific loss of GARP expression in mice results in cytokine dysregulation that is rescued by provision of wild type Treg cells. The knocked out region in this mouse model is homologous to the region that we identified as having an eQTL effect on GARP in our dataset.
Impact Our combined efforts have led to the definition of a functional role in Treg-mediated immunoregulation for a known autoimmune disease risk locus located in the human chromosome 11. Our results implicate Treg cells in the pathophysiology of human autoimmune and allergic diseases. Furthermore, we see this collaboration as very promising follow-up strategy for findings in additional loci. 2019 Update: We are currently working on a manuscript that will be submitted for publication to Nature. Provisional list of authors: 'Rabab Nasrallah, Francis Grant, Lara Bossini-Castillo, Firas Sadiyah, Dafni Glinos, Teresa Lozano, Panagiota Vardaka, Carina Nava, Hodaka Fujii, Derya Unutmaz, Enrico Lugli, Suman Mitra, Gosia Trynka and Rahul Roychoudhuri
Start Year 2018
 
Description European Molecular Biology Laboratory Heidelberg - Dr Judith Zaugg 
Organisation European Molecular Biology Laboratory
Department European Molecular Biology Laboratory Heidelberg
Country Germany 
Sector Academic/University 
PI Contribution I have provided the Zaugg team with quality filtered and processed ATAC-seq and histone (H3K4me3 and H3K27ac) ChIPmentation-seq data and defined the active chromatin regions in a subset of our samples. These samples comprised activated, cultured and primary regulatory T cells. Our team also provided processed RNA-seq data for the same individuals. We have contributed to the interpretation of results and development of their analysis framework. Moreover, we have provided a list of genes experimentally defined as differentially expressed specifically in Tregs.
Collaborator Contribution The Zaugg team have developed 'diffTF', a genome-wide method to assess differential TF binding activity and classifying TFs as activator or repressor by integrating any type of genome-wide chromatin configuration mark with RNA-Seq data and in-silico predicted TF binding sites (Berest et al. Genome-wide quantification of differential transcription factor activity: diffTF. 2017. Submitted). They are applying their method and expertise to our Treg resource.
Impact The aim of this collaboration is to identify differentially active transcription factors upon stimulation and culture in regulatory T cells, investigate activator/repressor classification of TFs based on RNA-seq and ATAC-seq data integration and construct gene regulatory networks in Tregs. The results and methods of these analyses will be publically available in the future, which will offer a framework to integrate multiple levels of genomic and transcriptomic sequencing data in general and to the knowledge about Treg biology in particular. 2019 Update: We are currently working on a manuscript to be submitted for publication in the following months. I am directly involved in the writing of the manuscript.
Start Year 2017
 
Description Primary immunodeficiencies - Newcastle University 
Organisation Newcastle University
Department Institute of Cellular Medicine
Country United Kingdom 
Sector Academic/University 
PI Contribution I will lead the analysis of both scRNA -seq and WES sequencing results obtained from one healthy control and two paediatric patients with Omenn's syndrome. One of the patients has an already known and quite frequent cause of Omenn's syndrome, i.e. RAG2-deficiency, and the second patient has mutation in a novel gene NUDCD3, which has not been published yet. The sequencing of these samples is being performed at the Wellcome Sanger Institute sequencing facilities.
Collaborator Contribution Our collaborators at the Institute of Cellular Medicine at the Newcastle University have provided us with the scRNA-seq libraries comprising FACS sorted T cells and B cells from the different individuals. Finally, they will also provide us with WES data from the patients and with clinical information that may help to interprete the results.
Impact This is a multidisciplinar collaboration with clinical geneticists, which will help to diagnose, characterise and maybe treat these patients. Moreover, this project will provide insights into the biology of the immune system by taking advantage of extreme phenotypes. The sequencing is being carried out at the moment and more patients are being recruited in parallel.
Start Year 2018
 
Description Stats-coloc 
Organisation King's College London
Department Department of Informatics
Country United Kingdom 
Sector Academic/University 
PI Contribution I contributed to the implementation of GoShifter (Trynka et al. 2015. Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci. American Journal of Human Genetics) into 'coloc-stats'. Coloc-stats provides a unified interface to perform colocalization analysis of genomic features using various analytical methods. It is implemented as a web server with a graphical user-friendly interface. I provided precomputed linkage disequilibrium data for the human genome build GRCh38 and collaborated in the testing and implementation of the method and options in the web server.
Collaborator Contribution Our collaborators created a web based interface including 7 colocalization methods: Genomic HyperBrowser & GSuite HyperBrowser, GenometriCorr, IntervalStats, GoShifter, LOLA, Stereogene and GIGGLE. They curated access and performance of the methods and allowed for proper comparison by the user of the results obtained with all the different methods. Finally, they led the manuscript writing.
Impact 2019 Update: This collaboration is multidisciplinary between Genetics, Informatics and Medicine departments. It resulted in a manuscript published in the 'Nucleic Acids Research' journal: "Coloc-stats: a unified web interface to perform colocalization analysis of genomic features." Simovski B, Kanduri C, Gundersen S, Titov D, Domanska D, Bock C, Bossini-Castillo L, Chikina M, Favorov A, Layer RM, Mironov AA, Quinlan AR, Sheffield NC, Trynka G, Sandve GK. Nucleic Acids Res. 2018 Jul 2;46(W1):W186-W193. doi: 10.1093/nar/gky474.
Start Year 2018
 
Description University of Chicago / AncestryDNA - Peter Carbonetto; University of Groningen - Lude Franke and Cisca Wijmenga 
Organisation University of Chicago
Country United States 
Sector Academic/University 
PI Contribution I am the lead analyst on this project which implements a pathway enrichment analysis on previously published celiac disease GWAS data using a Bayesian framework. Moreover, I identified a novel non-immune pathway and used a large gene co-expression dataset to gain further insight into the genes co-regulated in this pathway. 2019 Update: We established a new collaboration with the Teichmann team (Wellcome Sanger Institute) to include scRNA-seq from healthy human gut to this project with the aim of analysing the expression of the genes in the identified celiac disease enrichment pathways.
Collaborator Contribution Peter Carbonetto recently published a Bayesian framework approach to pathway analysis using GWAS data and collaborated for us to be able to implement it. I applied this method on celiac disease GWAS data provided by Cisca Wijmenga. Lude Franke provided me with a large set of expression data to explore the co-regulatory networks related to the enriched pathways in celiac disease. These collaborators contributed to the interpretation of the results and they are actively involved in the writing of the manuscript draft.
Impact This collaboration established a multidisciplinary connection between our group, which belongs to the cellular genomics division in Sanger, and a statistical methods oriented group in the University of Chicago. The writing of a manuscript including our results is in progress. Nevertheless, it has already resulted in a reviewer's choice awarded abstract in the ASHG 2016 congress. Moreover, I have personally benefitted vastly from this collaboration. I had the chance to interact with and learn how to use a completely new method directly from its developer, Dr Carbonetto. He was so kind to share with me his statistical expertise and advice, contributing greatly to my training and knowledge. Dr Lude Franke offered me guidance for the co-regulatory network analysis, which was an unexplored approach to me. 2018 Update -) A manuscript draft has been written and it is being corrected by the co-authors before submission. 2019 Update -) A new draft including the scRNA-seq data described above is being considered by the coauthors before submission
Start Year 2016
 
Description MSc Molecular Medicine at Sheffield University 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact Around 20 MSc Molecular Medicine students attended to an introduction to complex disease genetics. The presentation also included a brief description of my project. Interesting debate and questions were generated after the talk. The students showed great interest in the integration of the different levels of "omics" data to better understand the genetic architecture of complex traits.
Year(s) Of Engagement Activity 2016
 
Description School Videoconference (The Leys School) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact 35 minutes videoconference session with time for questions at the end for a science students class in The Leys School. The students had a particular interest in immunity / immune response and the advances in Genetics to understand the function and genetic control of the immune system. They read around the subject beforehand and asked questions at the end.
Year(s) Of Engagement Activity 2016
 
Description University of Cambridge Genomic Medicine Programme 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Postgraduate students
Results and Impact I taught an hour of in person theory to the students enrolled in the Genomic Medicine Programme Master's Degree Programme by the University of Cambridge. For an hour, I introduced the students into the basics of the functional role of non-coding genetic polymorphisms and their role in cellular phenotypes and disease. I explained to them the study design and methods included in my award. The students showed great interest in the subject and shared very good feedback about the lesson.
Update 2019 -) I was invited to teach a similar lesson in the 2018 course too.
Year(s) Of Engagement Activity 2017,2018