The page contains all the projects that are currently approved by the HostSeq DACO.
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Project Title: CGEn HostSeq – Canadian COVID-19 Human Host Genome Sequencing Databank
Principal Investigator: Lisa Strug & Lloyd Elliot
Affiliation: The Hospital for Sick Children
Project Summary: We hope to identify genetic differences that may explain why some people who get COVID-19 get really sick or have poor health outcomes and others do not. Using HostSeq datasets, we will analyze the genomes of patients to examine how variations in their DNA might be associated with their likelihood of becoming infected as well as with how their immune system reacted to the virus. We will use statistical and computational methods to analyze the requested datasets. We also plan to make our results available to other researchers to help them answer their important questions.
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Project Title: Cardiac Genome Clinic: a collaborative model for identifying the genetic basis of heart failure in the whole-genome era
Principal Investigator: Raymond Kim
Affiliation: The Hospital for Sick Children
Project Summary: Research on COVID-19 has established that the virus can cause a variety of cardiovascular disorders and myocardial injury in infected individuals. The Cardiac Genome Clinic (CGC) aims to utilize the HostSeq Database to identify genomic risk factors for individuals’ susceptibility to develop clinical cardiovascular manifestations of COVID-19 infection. The CGC will perform genome analysis on the HostSeq genomic data of individuals who were infected with COVID-19 and who have documented phenotypic data of having developed a clinical cardiovascular manifestation as a result. We will correlate genomic and phenotypic data to identify candidate risk factors for COVID-19 related cardiovascular disease. Finally, we will assess whether the candidate risk factors identified are present in our study’s internal database of individuals with non-COVID related cardiovascular disease, to assess whether the genomic risk factors may also be applicable to non-COVID populations. We will use the HostSeq genomic and phenotypic datasets to complete our study.
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Project Title: DeepHostSeverity: Deep learning and genomic driven COVID-19 severity assessment tool
Principal Investigator: Pingzhao Hu
Affiliation: University of Manitoba
Project Summary: Patients with COVID-19 show great differences in disease severity and clinical outcomes. Hence, a COVID-19 severity (i.e., vital status, ICU admission, ventilation utility) assessment tool is urgently needed. Recently, advanced genetic prediction tool, such as polygenic risk score (PRS), has been shown to be a significant promising way for predicting the risk of complex traits, but limited studies have been performed to use this strategy for COVID-19 severity. Here we will explore to develop artificial intelligence-based methods to calculate polygenic risk scores of complex traits. We will apply the approaches to analyze the whole genome sequencing data from CGEn HostSeq Databank to predict COVID-19 severity. We will also compare the performance of the model with that based on the phenotype data of the individuals from CGEn HostSeq Databank.
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Project Title: Population based evaluation of polygenic risk scores for common diseases
Principal Investigator: Jordan Lerner-Ellis
Affiliation: Mount Sinai Hospital
Project Summary: Common diseases such as diabetes, cardiovascular disease and cancer affect a substantial proportion of the population. These conditions are caused by a combination of genetic and environmental factors. A proportion of the population is at elevated risk for diseases due to the combined effects of multiple common genetic variants that each confer modest risk increases. The combined effect of many genetic risk variants can be used to construct polygenic risk scores (PRS). In particular, PRS for certain cancers, cardiometabolic disease, and other common diseases have demonstrated promise for identifying a proportion of the population at elevated genetic risk. In this study, we will calculate PRS using genome data from HostSeq databank and assess how well the PRS predict disease status.
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Project Title: Association studies exploring the relationships between specific HLA alleles, serology, and viral lineages on SARS CoV-2 symptom severity
Principal Investigator: Jordan Lerner-Ellis
Affiliation: Mount Sinai Hospital
Project Summary: HLA (Human Leukocyte Antigens) are proteins in the body that play a role in disease defense and specialize in detecting and eliminating foreign bodies. The genes involved in the HLA complex have a highly variable genetic code, meaning individuals in a population will commonly have slightly different sequences of these genes (called alleles). The HLA immune response is crucial against a viral infection such as SARS Cov2 that causes COVID-19, and different HLA alleles may result in a stronger or weaker immune response against the virus. The goal of this project is to discover any associations between specific HLA alleles, immune response and severity of COVID-19 symptoms. Identifying which alleles confer a stronger or weaker response may lead to more accurate targeted treatments, prevention and prophylaxis. HostSeq Data will be used in conjunction with GENCOV data to develop a large sample size thereby increasing the power to identify associations, and HostSeq Data will also be used for validation purposes for GENCOV specific study markers that may not be available through other participating HostSeq projects.
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Project Title: Clinically Relevant DNA Variation in the HostSeq Cohort
Principal Investigator: Jordan Lerner-Ellis
Affiliation: Mount Sinai Hospital
Project Summary: DNA biobanks developed for COVID-19 research have the potential to discover medically actionable findings that may be relevant not only for identifying individuals at high risk for COVID-19 related disease, but that also predict genetic conditions for which prevention, treatment or management strategies may be available. This study will identify the number and frequency of disease-causing and uncertain genetic variants identified in clinically relevant genes in an ostensibly healthy population. As genome sequencing becomes common place for population-based screening or diagnostic programs, this work will provide valuable insight into what types of clinically actionable genetic results may be identified and what implications they may have for individuals and families. This will help inform health programs on the utility of genome technology for personalized medicine.
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Project Title: Identification of repeat expansion in patients with severe COVID-19 using ExpansionHunter
Principal Investigator: Jordan Lerner-Ellis
Affiliation: Mount Sinai Hospital
Project Summary: Human DNA contains regions where patterns of nucleotides are repeated many times. The exact number of repeats varies from person to person, and when these repeats get too long, they can cause a class of diseases known as repeat expansion disorders. Almost 50 different repeat expansion disorders have been identified to date, and an important consideration of these disorders is clinical anticipation, which is when the severity of disease increases, and age of onset decreases through subsequent generations. Using ExpansionHunter, an algorithm that identifies repeats, and the GENCOV and HostSeq datasets, we will develop an algorithm that will determine if the repeat is disease causing, and return information about the diseases in which it has been implicated. This may shed light on a possible correlation between COVID-19 severity and repeat expansions.
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Project Title: Association study with genetic loci for COVID-19 and symptoms, severity, serology
Principal Investigator: Jordan Lerner-Ellis
Affiliation: Mount Sinai Hospital
Project Summary: During the past two years, COVID-19 has led to a worldwide crisis. One of the key challenges in controlling this pandemic is to determine why some COVID-19 patients are asymptomatic while others can be fatally ill. We aim to identify genetic factors that are associated with COVID-19 symptoms, severity, and immune response. Identifying such genetic markers could inform clinical care and targeted treatment development.
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Project Title: gnomAD-Canada, The Canadian Genome Aggregation Database
Principal Investigator: Jordan Lerner-Ellis
Affiliation: Mount Sinai Hospital
Project Summary: The Genome Aggregation Database (gnomAD) is a population database created by the Broad Institute that contains population frequencies of genetic variants in healthy populations and is a useful resource for understanding genetic variation in different populations and its relationship to disease. Historically, genomic studies have focused on populations of European ancestry, which is reflected in the population breakdown of gnomAD. As a result, gnomAD does not reflect the genetic diversity in populations that have been underrepresented in genomic studies, limiting its use as a reference for those populations. The HostSeq dataset will be used to create a Canadian version of gnomAD, called gnomAD-Canada. The creation of gnomAD-Canada will aid in increasing the genetic diversity and scale of genomic data available to the scientific community by including samples from historically underrepresented populations and help to create a reference database containing population frequencies of genetic variants in all populations.
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Project Title: The host genetic determinants of COVID-19
Principal Investigator: Brent Richards
Affiliation: Lady Davis Institute (McGill University)
Project Summary: While the COVID-19 pandemic has caused millions of premature deaths worldwide, most infected individuals only suffered a mild and uncomplicated illness. This range of clinical presentation is a hallmark of COVID-19 and is likely partially caused by underlying genetic susceptibilities to the virus. Understanding which genetic variants are associated with more severe disease may provide insights into the pathophysiology of COVID-19, which can be used to accelerate COVID-19 therapeutics development. Using common genetic variants, this approach has been used successfully to support the use of therapies currently in use for COVID-19 (e.g. interleukin-6 inhibitors). As part of the COVID-19 Host Genetics Initiative working group on whole-genome sequencing, we here propose to use modern genetic sequencing technologies to study rare genetic determinants of COVID-19. These should provide additional insights into how COVID-19 causes severe disease, and how we can better prevent and treat it.
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Project Title: In silico evaluation of the impact of pandemic-inherited study design biases with application to a thromboembolism-informed HD-GWAS of COVID-19 severe outcomes
Principal Investigator: France Gagnon
Affiliation: Dalla Lana School of Public Health (University of Toronto)
Project Summary: Considerable variability in symptoms and outcomes are observed among individuals infected by the virus SARS-CoV-2. One of the factors that partially explains this variability is the genetic make-up of an individual. Through analyzing the sequencing data of the human genome of thousands of Canadians, our study will help understand why some people manifest hospitalization COVID-19 while others develop mild non-hospitalization illness. We will focus on genomic regions related with thromboembolisms, which is the condition where a blood clot (thrombus) formed in a vessel travels through the blood causing an obstruction. The frequency of thromboembolism in COVID-19 individuals is high and it is associated with increased risk of death. However, defining the causal risk factors of a new disease, as COVID-19, is challenging because the participants are recruited from different studies across the country with their own diagnosis methods, disease severity definitions, periods of time, etc. The variability criteria between the studies can impair the precise association of the exposure (genetic factor) with the disease. Thus, we will also evaluate how differences among studies designs can injure finding true genetic risks with COVID-19.
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Project Title: Post COVID hyperinflammation: A syndrome beyond the name (STOP MIS-C)
Principal Investigator: Rae Yeung
Affiliation: The Hospital for Sick Children
Project Summary: COVID-19 can cause a life-threatening Multisystem Inflammatory Syndrome in Children (MIS-C) typically weeks after a mild or even asymptomatic infection. Each wave of COVID-19 cases is closely followed by a wave of previously healthy children presenting to hospital in shock and heart failure due to uncontrolled inflammation. The new syndrome closely resembles Kawasaki Disease (KD). Similar to KD, the heart is one of the key organs affected with 1 in 3 children needing intensive care management for heart failure, and 1 in 4 children developing coronary artery inflammation and damage. It is critical to enable health care teams to rapidly recognize MIS-C, identify high-risk children and control life-threatening inflammation before it damages the child’s heart. Our team has studied and dissected the reasons responsible for inflammation leading to shock and hyperinflammation in KD and have identified key biomarkers and targets for treatment. These have been rapidly translated to the bedside resulting in new medications and improved outcomes. These lessons have been transferred to MIS-C, providing the evidence to guide development of effective therapeutic approaches. Our team includes doctors, scientists, and families working together to tackle this serious disease. We will use machine learning and artificial intelligence to analyze biologic/genomic and clinical data to rapidly diagnose MIS-C and predict which child will develop severe disease. We’ve done this before in other diseases and already have a strong and deeply committed Canada-wide team, expertise and infrastructure in place from our other projects and networks. We have partners in Europe and the USA, where we can learn from each other and be most efficient and not have to reinvent the wheel. We will seamlessly share information to rapidly improve care for affected children around the world.
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Project Title: Covid-19 genome analysis
Principal Investigator: Inanc Birol
Affiliation: BC Cancer
Project Summary: COVID-19 is a highly lethal viral pandemic caused by SARS-CoV-2 coronavirus. Although the virus strains are being rapidly sequenced for tracking and vaccine development, little is known about host susceptibility to SARS-CoV-2 infection. In this project we address this gap. The Human Leukocyte Antigen (HLA) genes play an important role in our immune systems. These genes are key to many aspects of human physiology and medicine, including our body’s response to infections. HLA genes show high variability between individuals and groups. While much attention has been on how existing health conditions of patients impact clinical outcomes, contribution of variability in HLA genes to these outcomes is under-studied. Here, we explore the link between variations in the HLA genes in a large group of COVID-19 patients whose genomes are sequenced as part of the Canadian COVID Genomics Network. We investigate patterns of HLA variants associated with disease development, severity, and mortality.
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Project Title: Dissecting the genetic architecture of COVID-19 comorbidities and identifying biomarkers for high-risk individuals
Principal Investigator: Celia Greenwood
Affiliation: Lady Davis Institute for Medical Research
Project Summary: A significant proportion of the population has been affected by COVID-19 both in Canada and worldwide. Although most COVID-19 infections are not life-threatening, a large number of COVID-19-related mortality has occurred. It is therefore important to understand who are more likely to suffer from severe symptoms and to explore approaches to mitigate illness amongst these people. Based on clinical observations, some pre-existing chronic diseases (comorbidities), such as Alzheimer’s disease or dementia, chronic pulmonary diseases, hypertensive and cardiovascular diseases, and diabetes, might contribute to increased COVID-19 mortality. To better understand the role of comorbidities in disease manifestation and progression, we will characterize genetic factors driving the heterogeneity of COVID-19 comorbidities within the Canadian population and assess how they are associated with COVID-19 clinical outcomes. Using genetics-based causal inference methods, we will also attempt to identify potential predictive biomarkers and drug targets specifically for individuals having adverse comorbidities.
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Project Title: Cluster analysis of patients infected by COVID-19 and a risk forecast model based on clustering
Principal Investigator: Sanjeena Dang
Affiliation: Carleton University
Project Summary: Patients infected by Covid-19 have a diverse range of symptoms and severity, varying from mild cough to fatal complications. To understand variation in the response to COVID-19 infections, it is important to understand and characterize the variations among these patients with respect to the demographic information as well as other comorbidities. Using the dataset from CGEn Host Genome Sequencing Initiative, the proposed research will focus on: Aim 1: Cluster individuals into different groups/classes based on comorbidities, demographic information, and clinical assessments and characterize these clusters. Aim 2: Identify genetic risk variants for developing severe COVID-19 outcomes. Unique characteristic genomic regions will be identified and used to build a predictive model for various levels of severity in COVID-19 response. Identifying individuals who are most at risk and prioritizing appropriate treatments in a timely manner to high-risk individuals could be valuable in developing resource allocation strategies and minimizing adverse health outcomes.
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Project Title: HostSeq as a Canadian population control for comparative studies of autism spectrum and related disorders.
Principal Investigator: Stephen Scherer
Affiliation: The Hospital for Sick Children
Project Summary: Our current studies which aim to determine the role of genetic variation in complex neurodevelopmental disorders require access to a large number of patient samples in order to capture the full spectrum of genetic changes which may contribute to these disorders. Equally important, is having access to a sufficiently large number of unaffected and unrelated population control samples for comparison. Having access to whole genome sequencing data from a large set of clinically unaffected samples for comparison (HostSeq) will help to further identify and characterize the role and impact of genetic variation in ASD and other related neurodevelopmental disorders.
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Project Title: Genetics of Mortality in Critical Care (GenOMICC)
Principal Investigator: David Maslove
Affiliation: Queen’s University
Project Summary: While some patients who get COVID-19 experience only mild symptoms, others develop severe illness, sometimes requiring advanced life support, including ventilator care in an ICU. Prior studies suggest that the propensity to develop critical COVID-19 is at least in part genetically determined. Through this study, we will further investigate the genetic traits associated with critical illness, in a diverse population of Canadians with COVID-19. Our results will help deepen our understanding of COVID-19, and lead to better treatments.
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Project Title: Investigating human genetic variation in phosphorylation sites in association to SARS-CoV-2 infection
Principal Investigator: Juri Reimand
Affiliation: Ontario Institute for Cancer Research
Project Summary: Human genomes have small differences that determine the many features we have inherited, including disease risks of COVID-19. We hypothesize that some of these differences in individual genomes also determine how proteins in our cells interact with one another in complex interaction networks. Previous studies since the start of the pandemic have mapped the molecular interaction networks involved in virus infection and the human responses to infections as well as the COVID-19 disease. In this project, we will use HostSeq data to study individual genetic differences through the lens of these disease-associated molecular interaction networks. We will use AI tools our lab and others have developed to learn about such genetic variants and their potential involvement in infections and disease. Our research will help us better understand how SARS-CoV-2 infects humans and how our genetic differences may contribute to disease risk and outcomes.
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Project Title: Hereditary Cancer and Genetic Variation in Canada – A genomic populational study
Principal Investigator: My Linh Thibodeau
Affiliation: BC Cancer
Project Summary: Cancer affects 2 in 5 Canadians during their lifetime. Approximately 10% of all cancers are caused by a familial (or “germline”) genetic mutation which can be passed down the generations. Knowing who has a familial genetic mutation predisposing to cancer is helpful to provide optimal genetic counselling, cancer surveillance, prevention and if cancer happens, the best cancer treatments. Identifying families at higher risk of cancer is challenging since some individuals have little information about the cancer diagnoses in their families. There is a lack of information and numbers (“statistics”) on the frequency of cancer risk familial mutations in Canada. Using the HostSeq DataBank (genetic information of >10,000 Canadians), we will assess the frequency of cancer risk familial mutations across Canada. This research will advance our understanding of genetic diversity (“variation”) in Canada and may provide new and unexpected information to facilitate clinical genetic testing access for some Canadians.
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Project Title: Characterizing and navigating the landscape of genomic ‘secondary findings’ in pediatric cancer patients of diverse backgrounds
Principal Investigator: David Malkin
Affiliation: The Hospital for Sick Children
Project Summary: Over the last decade, genomic sequencing of childhood cancers has yielded dramatic insights into their molecular processes and underpinnings; however, the discovery of genetic mutations not known to be related to the biology of a patient’s cancer remains a prevalent, unavoidable consequence. These genetic mutations are known as “secondary findings” (SFs) and often poorly understood because of the rarity of childhood cancers and limited availability of genetic data. However, many SFs are potential predictors of significant life-threatening diseases that can be managed or treated and can help doctors improve the health of their patients. We still do not know which SFs are most frequently found in children with cancer, the impacts SFs may have on overall health, or whether SFs may alter the prognosis or treatment of pediatric cancer patients. We are investigating the landscape of SFs to reveal new roles for these understudied genetic mutations and inform healthcare practices.
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Project Title: Genomic assessment of pulmonary and renal complications during COVID-19 hospitalization
Principal Investigator: Nathan Yoganathan
Affiliation: JN Nova Pharma Inc.
Project Summary: Vaccinations are effective in controlling the spread of COVID-19, but there are limited treatment options for individuals who contract the virus. This is particularly concerning for patients with pre-existing conditions (e.g. cardiovascular, lung, kidney, diabetic) as COVID-19 can harm several organs if left untreated. This group of patients, who make up over 80% of hospitalized patients, is at a higher risk of death. Our medical treatment neutralizes and traps the coronavirus and stops it from entering the lungs, while also helping the body’s immune system fight the virus. This can help protect against kidney injury and improve recovery from lung failure and potentially aid patients with long COVID. To optimize the use of this treatment, we will use the HostSeq Databank to identify patients who are at risk of lung and kidney complications during hospitalization and would benefit from this treatment.
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Project Title: Solving the genomics of unsolved rare life-threatening COVID-19 using genome sequencing
Principal Investigator: Gerald Pfeffer
Affiliation: University of Calgary
Project Summary: COVID-19, caused by the SARS-CoV-2 virus, has been declared a pandemic and is one of the most urgent global health crises. The phenotypes of COVID-19 are highly heterogeneous, and a major challenge is the early recognition of severe COVID-19 to support early clinical intervention and targeted therapy. Certain individuals may have a higher risk of severe disease, for example, people with pre-existing respiratory, cardiac, or immune disorders. However, in some rare cases, severe disease occurs in young individuals without any risk factors and is unexplained. We hypothesize that severe illness with COVID-19 in people who do not otherwise have pre-existing risk factors is attributable to monogenic causes in some cases. We have an opportunity to study this in participants recruited to the Alberta Host Genetic Susceptibility project (led by Pfeffer lab) within Hostseq, which focused on younger patients who required hospitalization and did not have pre-existing comorbidities. We will apply cutting-edge genome sequencing (GS) analytical approaches developed by Tarailo-Graovac lab with correlation to comprehensive clinical data. We have successfully applied GS methods to unravel the complex genetic mechanisms underlying rare undiagnosed diseases by identification of previously missed variants of interest. I will work with genomes of the rare severe patients with COVID-19 using the “three stages” and “two levels” strategy to identify causative genes and complex genetic scenarios in independent cohorts. We will apply the background variant information from the Hostseq database to help narrow down the candidates. As such, this work has the potential to build a diagnostic workflow for rare, life-threatening COVID-19 patients and provide clues for identifying individuals predisposed to severe COVID-19 outcomes.
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Project Title: Comprehensive RNA-seq profiling of COVID-19 patients: combining microbial diagnostics with host genetics determinants of disease severity
Principal Investigator: Andrew Doxey
Affiliation: University of Waterloo
Project Summary: It is of critical importance to predict whether or not an individual infected with SARS-CoV-2 is at risk for severe COVID-19 symptoms. Research suggests that an individual’s genetics may be a major influence on their disease susceptibility, and so this research project is going to examine this hypothesis further using public genetic information and COVID-19 clinical data for Canadian individuals available in the HostSeq database.
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Project Title: Host genomic determinants of severe COVID-19
Principal Investigator: Stuart Turvey
Affiliation: University of British Columbia
Project Summary: Most people with COVID-19 have mild symptoms or no symptoms at all, but some individuals get very sick and can even die. This can be influenced by changes in the genetic makeup of the affected individuals, the virus itself, as well as other factors like their lifestyle and health risks. Previously healthy individuals with really severe outcomes of COVID-19 might have an underlying genetic problem that has not caused any symptoms before, but makes them more vulnerable to the virus now. Using HostSeq Databank, we will study linked genetic data from the affected individual (and their virus) along with their health information to understand how changes in their DNA might put them at an increased risk of developing a severe response to COVID-19 infection.
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Project Title: Post-acute COVID-19 in the province of Ontario: Estimation of prevalence and identification of risk
Principal Investigator: Jennifer Brooks
Affiliation: University of Toronto
Project Summary: More than 10% of people who have had COVID will go on to experience what is known as “long COVID”. Identifying and understanding the risk factors for experiencing long COVID is essential to understanding long-term outcomes from COVID-19 infection(s). This will inform our understanding of the health care needs of patients following acute COVID illness, allowing for sustained support and early intervention to improve outcomes. We are planning to use the questionnaire and genetic data from the Host-Seq project, linked with administrative health data (generated when patients interact with the health system) to better understand this phenomena. In particular we are interested in identifying genetic variants associated with an increased risk of long- COVID.
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Project Title: Improved Understanding of the Genetic Etiology of Cardiac Conditions using HostSeq as a Control Dataset
Principal Investigator: Raymond Kim
Affiliation: The Hospital for Sick Children
Project Summary: The Cardiac Genome Clinic is a research cardiac genetics clinic in Ontario. Researchers in the Cardiac Genome Clinic use genetics to understand why some people develop heart problems. To do this, they want to see if some genetic findings are more common in people with heart problems than in people without heart problems. The Cardiac Genome Clinic already has a group of research participants who have heart problems and DNA sequencing. They need a comparison group of people without heart problems to better understand what may have caused heart problems in their cohort. They will use a subgroup of participants in the COVID-19 HostSeq database to serve as this comparison group. The overall goal is to better understand the genetics of heart disease to use this information to better care for patients. This is also important for patients with COVID-19 infections because the virus may impact the heart for some.
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Project Title: Understanding the genetic background of synucleinopathies and their progression
Principal Investigator: Ziv Gan-Or
Affiliation: McGill University
Project Summary:
Synucleinopathies are a group of diseases including Parkinson’s disease (PD), dementia with Lewy bodies (DLB), REM-sleep behaviour disorder (RBD) and others. In this study, we aim to understand how our genetic background affects our risk for developing these disorders and how they progress. For example, individuals with RBD will progress to PD or DLB within 10-12 years on average.
However, some individuals progress much faster than others, and we hypothesize that our genetic background has a major effect on the progression of these disorders. Our study will enable us to detect specific genes that are involved in these disorders, which can then become targets for drug development.
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Project Title: Characterizing the human virome in European and Japanese cohorts using unmapped reads from whole genome sequencing
Principal Investigator: Guillaume Bourque
Affiliation: McGill University
Project Summary: Humans are constantly infected by viruses. Our hypothesis is that viral reads can be extracted from whole genome sequence data and could be used to try to detect the presence of viruses and study their association to various phenotypes, including genetic factors. In this study we will perform various association studies between these reads and various factors such as genetic variants, age and sex, blood test results. In the end, we are hoping to be able to report factors that contribute to the risk of infection.
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Project Title: HostSeq as a Canadian population control for studying the genetics of adolescent idiopathic scoliosis
Principal Investigator: Kamran Shazand & Stephen Scherer
Affiliation: Shriner’s Children’s Genomics Institute & The Hospital for Sick Children
Project Summary: Adolescent idiopathic scoliosis (AIS) is a condition in which the spine becomes curved. As its name suggests, it starts to occur during a person’s teenage years (adolescence) and has no obvious cause (idiopathic). To better understand why AIS occurs, we will use genome sequencing data from individuals with AIS and their family members. This data will be compared to people from the HostSeq project (who do not have AIS) so that we can identify differences in the genetics of people with AIS compared with people without it. The genetic variants we identify will be evaluated in animals such as zebrafish to better understand their role in AIS.
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More project details will be added as they get approved.