Academic research community (GECIP)

Genomic medicine has the potential to improve prediction and management of chronic conditions, particular those with a strong genetic component. Thoracic aortic disease (TAD) is one such condition – it is often silent until a catastrophic life-threatening complication occurs (such as dissection or rupture), and genetic information can inform both identification and treatment of the disease at an early stage. There are a number of challenges in assigning causality to genetic variants and or prioritising further studies in TAD. Aortic tissue is not routinely available, and signs and symptms of early disease may be subtle. Aortic vascular smooth muscle cells created from stem cells from patients with Marfan Syndrome, developed in Cambridge, provide a powerful model that lead failure of the aortic wall. These models provide an opportunity to study variants identifed from patients in the 100,000 Genomes Project. In our first aim, we will use stem cell models and techniques to alter DNA we are able to study how disease variants affect structure of smooth muscle cells and then analyse the impact on function. We will then create a platform that will allow assessment of multiple variants at the same time to help characterise if they lead to disease or not. Finally, we will use innovative bioengineering techniques to create blood vessels that will allow us to study these diseases in a 3D form. Ultimately, the aim of this technology is to provide rapid diagnosis to patients with TAD and develop a system that we use to predict how severe disease will be. The work in this project will contribute to creating blood vessels in the lab which one day may be used for bypass operations.

Heart failure is a debilitating chronic condition affecting at least 920,000 people in the UK. The aim of this project is to investigate how genetic and non-genetic factors combine to influence the risk of heart muscle disease and heart failure. In prior work, through an international collaboration for heart failure genetics, we have shown that common genetic variation is important; this project seeks to understand whether genetic information may help to better predict heart muscle disease and heart failure in populations at risk, such as patients treated with cancer medicines that can cause damage to the heart. If successful, this work may support the development of clinical prediction tools to guide preventive medical interventions.

Cardiomyopathies (CMPs) are a heterogeneous group of diseases characterized by impairment of heart muscle function. CMPs has prevalence of 1:500 to 1:2500 in general population. To understand the changes in the DNA sequences that lead to CPMs, to date researcher have focused on the part of the DNA that codes for the protein, known as genes, as these changes are easy to interpret. This approach resulted in understanding cause of disease in 30% of the CMP individuals, however, majority of the cases still remain genetically undiagnosed. Suggesting that changed in DNA sequence outside the gene region may explain some of the genetically undiagnosed cases. Genes are regulated by specialized parts of DNA called as enhancers that are located far away from the genes. The enhancers control the amount of mRNA produced from genes and subsequently the protein. Changes in DNA sequence of these control elements could lead to reduced or increased production of proteins than required for normal development and functioning of the heart. Altered amount of mRNA production may lead to disease phenotype such as CMPs. In this study, we aim to identify defects in such regulatory elements, specifically in heart, that lead to CMPs. This study will identify novel disease associated regions, which could help not only to increase the diagnostic yield significantly but also could help disease treatment and management.

Genetic DCM epidemiology data is elusive and confirm the difficulty to know the “real” prevalence of this entity in the overall scope of heart failure (HFrEF) and general population. Our aim is thus to investigate the prevalence and the phenotypic characteristics of patients with DCM of genetic aetiology in general as well as characterise the contributions of the various specific mutation types to the genetic DCM prevalence.

Dilated cardiomyopathy (DCM) is a condition where the heart dilates and its pumping function is weakened. In up to 40% of people this has an identifiable genetic cause. A subset of patients with DCM appear at increased risk of life-threatening heart rhythm disturbances, which may be excessively slow or fast. Some patients may be offered an internal defibrillator (ICD) to protect them from some of these rhythm disturbances. It remains difficult to accurately predict who will benefit most from an ICD. The aim of this study is to evaluate whole genome data collected through the 100,000 Genomes Project, in combination with clinical data, to see if this can help predict the risk of life threatening heart rhythm disturbances.

Hereditary transthyretin-mediated amyloidosis (hATTR) is an underdiagnosed and progressive debilitating disease caused by the accumulation of variant, misfolded TTR proteins into intracellular plaques. These plaques can lead to neuropathies that often first present as carpal tunnel syndrome and then progress through increasing levels of numbness in feet and hands. In the most severe cases the progression leads to complete immobility and death. TTR plaques can also form in the heart and lead to progressive cardiac dysfunction and ultimately death. Many variants of the TTR gene are known and several are associated with amyloidosis disease. The V122I variant of the TTR gene is common among individuals of African descent and has traditionally been associated with heart disease. Recent analyses of large human genetics databases available to Alnylam, including the UK Biobank, the UPenn Biobank, and the US Million Veteran Program (MVP), which includes a large number of African-Americans, demonstrated a clear association between the V122I variant in neuropathies as well. Our analyses also identified additional TTR variants as well as the relationship between the genetic makeup and the course of disease onset and progression. Effective TTR amyloidosis therapeutics have recently emerged that mitigate and in some cases reverse disease burden of TTR amyloidosis. One therapeutic strategy employs a molecule that stabilizes the TTR protein, which in turn slows the accumulation of the plaque and mitigates disease progression. Alnylam’s strategy relies on a novel therapeutic modality referred to as ‘RNA interference’ or RNAi. RNAi therapeutics stop the production of the TTR protein by specifically cleaving the RNA molecule that codes for the TTR protein and have demonstrated the ability to reverse the course of the amyloidosis. We want to extend our genetic analyses to the data in the NGRL. amyloidosis, better understand the relationship between distinct TTR variants and disease progression, and provide a direct clinical benefit from administration of novel therapeutics.

We propose to combine calculation of genetic risk metrics (measuring each participant’s genetic predisposition for a set of obvious, observable, and measurable trait)s with patient medical record data to identify characteristics of diseases and their associated mechanisms, outcomes, and clinical progression. This project is focused on Cardiovascular Disease. We propose to investigate in the following areas.1. Compute genome-wide predictions for a panel of relevant traits: Genome-wide Polygenic Risk Scores (PRS) reflect a quantitative measurement of the tendency to develop certain phenotypic traits, e.g., certain blood biomarkers, by aggregating across usually a large number of genetic loci that are known to be related to a specific phenotype in a weighted manner. PRS study can shed light on the disease causal mechanism from the commonly occurring genetic variants. Normally these kinds of genetic loci will have very little impact on the phenotype individually. However, combined together, these loci can help us disentangle the molecular mechanisms behind certain diseases. 2. Analyze the genetic variants/variants that cause a potential loss of function of the protein products within a given disease cohort. While certain genetic variants have minimal functional impact individually (see bullet 1), other variants significantly impact the function of the protein products of disease-relevant genes. This type of variants are predicted Loss of Function variants (pLoF). Individual LoF variants repeatedly occurring on the same gene or gene pathways across patients with similar disease phenotypes provide evidence of the involvement of those molecular processes in the etiology of disease. PRS analyses (bullet 1) coupled with analysis of pLoF variants will give us a robust picture of likely molecular causes of Cardiovascular Disease. 3. Take the insights from the 100,000 Genomes Project participant data and combine with insights from other datasets we work with (for instance adding detailed medication information or rich biomarker data, to supplement the genetic data in the NGRL). Pooling all of this together helps us run our advanced algorithms to produce more detailed biological and therapeutic insights related to Cardiovascular Disease. Ultimately, the goal of this work is to match the right patients to the right therapies at the right time, and to identify unmet needs and associated potential points of intervention. 4. Engage with patients directly. We believe that we must not only identify disease-modifying interventions targeting the mechanisms underlying each patient's specific disease, but that we must also understand the manifestation and impact of these mechanisms on each patient's journey--for instance via devices and patient-reported outcomes--in order to better measure, model, and treat the ooutcomes that matter most to each person in the context of their lives and their disease.

Something missing? The aim of this study is to look at the genetic variants associated with effective pharmacotherapeutic treatment for hypertension in the PAFOD in the UK. The objectives are to search and Identify the black african population, and white british as control sample in Genomics England (GeL) 100,000 Genomes database that has hypertension, and also Examine their HES, and Perform the variant call analysis with sample data to identify SNPs and any rare variants in black africa sample.

The project aims to investigate the potential genetic link between cardiomyopathies and autoimmune disease through assessment of the collective burden of common risk alleles underlying the main autoimmune diseases (collectively and per disease) in the cardiomyopathy patients sequenced as part of the 100,000 Genomes Project. For these analyses we will select a control group of individuals without cardiomyopathy and / or a disease phenotype linked to inflammation. Using a similar approach the project will also assess the burden of common risk alleles associated with the major risk factors for cardiomyopathy which include high blood pressure, heart disease, heart failure, diabetes, and severe obesity.

Why do some diseases have symptoms at particular times of day? All people have a biological clock that synchronises their body with the daily cycle of day and night. This is called the circadian clock. The effects of your circadian clock being out of synch with the environment can be seen most obviously with the phenomena of jetlag. However, the circadian clock is important for the correct functioning of all the cells in your body. We are working to identify how the circadian clock affects people with rare diseases. We call this merging of genomic medicine and chronobiology “chronomic medicine”. We are looking at different ways that this can happen. Different groups of people are genetically programmed to do things earlier or later in the course of the day. This is called a person’s chronotype. People may be familiar with the popular terms used to describe this – “morning lark” and “night owl”. An increasing number of indicators of health and disease are becoming associated with a person’s chronotype. We are identifying which genetic diseases are associated with chronotype, and the likelihood of getting a severe coronavirus infection. The circadian clock is found within every cell, but controlling different genes depending on the tissue or organ under observation. There is a master clock in the brain that synchronises the rest of the body with hormones that rise and fall every day. The genes that control this clock can also cause diseases for example sleep disorders. However, whether these genes cause other diseases in different tissues is unexplored. Around 40% of the genes in your body change what they do over the course of a day. The bit of a gene that contains this information for controlling a gene contains activity across a gene is called a promoter. Within this promoter are elements that make the activity of that gene oscillate across the day. Many diseases show different severity in different people, and at different times of day. We have found differences in these regions in people with rare genetic diseases which show time of day effects have which might explain why the gene behaves differently. We have worked to identify candidate diseases for prioritisation for chronomic medicine. Our previous work has identified inherited cardiac arrhythmia syndromes as good candidate diseases. We are looking at whether these diseases, such as Long QT syndrome, have more people with early or late chronotypes, and whether this is associated with the severity of the disease. We have identified some changes in the promoters of a key gene in Long QT Syndrome that may control whether changes in levels of that gene change over over a day that are very common in people with arrhythmias, but not in other people. We are studying how these variants affect the daily timing of these important disease genes, and how they might affect the expression of the gene like a dimmer switch. This project is identifying how our relationship with the day night cycle impacts rare diseases. It will lead to possible routes for new non-invasive therapies, by optimising the time of day that existing therapies are given.

Since the initial reports in December 2019 from Wuhan (China) of a new viral infection leading to a fatal condition (COVID-19) initially recognised as pneumonia, many questions remain unanswered. However, the virus (SARS-CoV-2) shares many similarities with other previously reported viruses causing related clinical syndromes SARS and MERS. Recent studies suggest the Spike (S) protein on the virus directly interacts with the ACE2 protein on the surface of nearly all human cells. This, along with other proteins ensure the virus particle enters the host cell and replicates. It is widely accepted, based on studies of many known viruses, that genetic variants in the host play an important role in viral entry and subsequent replication. Furthermore, this might also explain the wide ranging differences in susceptitibility, presentation, progression and outcomes for COVID-19 patients. This study will investigate the genetic code of patients to identify patients who might either be most at risk or largely resistant to COVID-19. In particular, we will attempt to correlate the genetic findings with cardiovascular phenotypes. It is hoped this will lead to better diagnosis, prognosis and eventually novel therapies.

The Msc in Genomics Medicine at the University of Sheffield plays an important role in training future bioinformatics staff. This project will be for an Msc student with an interest in cardiovascular genetics. Some of these conditions can affect the heart muscle or the aorta (main artery leading out of the heart). These conditions can run in families and identify any genetic cause has an important implication for management of relatives. In this project the student will examine genome sequencing data from people with potential cardiogenetic disease to see if a likely cause can be identified. These will then be validated in our clinical laboratory.

Rare disease and cancer genomes will be analysed for low frequency or rare variation in arrhythmia genes at a single variant level, and then gene or gene network level if appropriate. The main LQTS, BrS and CPVT genes will be studied as well as minor arrhythmia genes. Associations with Human Phenotype Ontology (HPO) terminologies, secondary healthcare data outcomes and drug exposure data will be studied to assess genomic and pharmacogenomic risks for arrhythmia and sudden death. A Phenome Wide Association Study (PheWAS) will then be conducted to identify novel associations with other disorders such as psychiatric and neurological disease. Novel variants associated with risk will be studied for functional effects and correlated with the relevant association. A population method for clarifying variant pathogenicity will be established.

Proband singletons will be reviewed for arrhythmia phenotypes for tier 1 and 2 variants. They will be classified as either pathogenic, likely pathogenic or as a variant of uncertain significance (vus) according to ACMG criteria. To determine whether variants had been detected previously, queries will be made to the GMC and detail regarding study design of any genetic testing that may have taken place will be identified. This study will determine whether additional results are produced from WGS and if this is a result of coverage issues or limitations of gene panel range.

This project will identify genomic changes which inhibit the normal activity of a gene, but isn't included in the protein-coding regions. These regions haven't previously been surveyed comprehensively. We will also investigate the variability in disease associated with these types of genomic changes.

The International Mouse Phenotyping Consortium is investigating what happens when individual genes in the mouse are removed. Many of the genes are also present in human and may be expected to show the same disease phenotypes if a patient has a mutation in the gene. Hence these screens can highlight novel candidates when analysing the genomes sequenced as part of the 100,000 Genomes Project. As part of the mouse screen, congenital heart disease phenotypes are investigated and we have identified 95 novel genes that have not previously been implicated in this disease in humans. Here we screen the congenital heart disease patients in the 100,000 Genomes Project cohort for disrupting and de novo variants in these novel genes that may explain their condition.

Cardiovascular disease presents a global health burden. The genetics causes of many cardiovascular diseases remain unknown. A group of genes which function in controlling other genes have been shown to be mutated in congenital heart disease (a group of diseases where the heart is formed incorrectly during development). In this project these genes will be studied for variants in both congenital heart disease and other cardiovascular conditions. This will contribute to understanding the extent of which this family of genes contributes to cardiovascular disease and the role they play in the heart. This is important in order to understand these conditions for both genetic counselling and treatment purposes.

Brugada syndrome (BrS) is a disease that causes malignant arrhythmias and sudden cardiac death (SCD) in young individuals. It was originally described as a purely electrical disease that did not cause structural alterations. Recent studies, however, have shown the presence of scar and inflammatory infiltrates in the hearts of BrS patients. Inflammation was recently shown to be a major driving force in another disease, arrhythmogenic cardiomyopathy (ACM), which shares both clinical and genetic features with BrS. In a pilot study we showed significant changes in the levels of selected pro-inflammatory mediators in the serum of BrS patients compared to healthy controls. We now need to confirm and validate these findings in larger patient cohorts. This would significantly advance our knowledge on pathways of disease pathogenesis as well as provide new diagnostic markers and potential therapeutic targets. Professor Hamilton of the Hospital for Sick Children in Toronto, Canada recently identified four circulating auto-antibodies in a small number of BrS patients. These appear to be specific to BrS as they are absent in control sera or sera from patients with other forms of heart disease. Validation of these findings in additional samples could form the basis for the development of a reliable assay for detection of BrS in patients undergoing evaluation. Despite decades of research, diagnosis of BrS remains challenging owing mostly to lack of understanding of disease mechanisms. Our studies are anticipated to shed light to molecular pathways of disease aiding both accurate diagnosis and forming the basis for much-needed mechanism-based therapies in an effort to ultimately reduce the occurrence of SCD in our society.

Current clinical genetic testing for cardiomyopathies focus only on protein-coding variants, finding a disease-causing variant in around 30% of all cases. There is a great interest and potential to extend the investigation to non-coding variants. This project aims to build a map of non-coding regulatory regions for cardiomyopathy genes, aiming to discover new pathogenic variants and expand our understanding of the genetic aetiology of cardiomyopathy.

The 100,000 Genomes Project provides an unprecedented opportunity to explore the genetic basis for complex diseases. Our approach focus on specific regions of the genome which regulate the expression of individual genes. We will use information from various databases as well as develop bioinformatic approaches and use experimental data to pinpoint regions of the genome for detailed interrogation. We will test experimental genes in the lab using various model systems.