Using molecular QTLs to identify cell types and causal variants for complex traits

Genetic associations have been discovered for many human complex traits, and yet for most associated loci the causal variants and molecular mechanisms remain unknown. Studies mapping quantitative trait loci (QTLs) for molecular phenotypes, such as gene expression, RNA splicing, and chromatin accessibility, provide rich data that can link variant effects in specific cell types with complex traits. These genetic effects can also now be modeled in vitro by differentiating human induced pluripotent stem cells (iPSCs) into specific cell types, including inaccessible cell types such as those of the brain. In this thesis, I explore a range of approaches for using QTLs to identify causal variants and to link these with molecular functions and complex traits. In Chapter 2, I describe QTL mapping in 123 sensory neuronal cell lines differentiated from human iPSCs. I observed that gene expression was highly variable across iPSC-derived neuronal cultures in specific gene categories, and that a portion of this variability was explained by commonly used iPSC culture conditions, which influenced differentiation efficiency. A number of QTLs overlapped with common disease associations; however, using simulations I showed that identifying causal regulatory variants with a recall-by- genotype approach in iPSC-derived neurons is likely to require large sample sizes, even for variants with moderately large effect sizes. In Chapter 3, I developed a computational model that uses publicly available gene expression QTL data, along with molecular annotations, to generate cell type-specific probability of regulatory function (PRF) scores for each variant. I found that predictive power was improved when the model was modified to use the quantitative value of annotations. PRF scores outperformed other genome-wide scores, including CADD and GWAVA, in identifying likely causal eQTL variants. In Chapter 4, I used PRF scores to identify relevant cell types and to fine map potential causal variants using summary association statistics in six complex traits. By examining individual loci in detail, I showed how the enrichments contributing to a high PRF score are transparent, which can help to distinguish plausible causal variant predictions from model misspecification.Wellcome Trust Sanger Institut

Intellectual disability associated with a homozygous missense mutation in THOC6

BACKGROUND: We recently described a novel autosomal recessive neurodevelopmental disorder with intellectual disability in four patients from two related Hutterite families. Identity-by-descent mapping localized the gene to a 5.1 Mb region at chromosome 16p13.3 containing more than 170 known or predicted genes. The objective of this study was to identify the causative gene for this rare disorder. METHODS AND RESULTS: Candidate gene sequencing followed by exome sequencing identified a homozygous missense mutation p.Gly46Arg, in THOC6. No other potentially causative coding variants were present within the critical region on chromosome 16. THOC6 is a member of the THO/TREX complex which is involved in coordinating mRNA processing with mRNA export from the nucleus. In situ hybridization showed that thoc6 is highly expressed in the midbrain and eyes. Cellular localization studies demonstrated that wild-type THOC6 is present within the nucleus as is the case for other THO complex proteins. However, mutant THOC6 was predominantly localized to the cytoplasm, suggesting that the mutant protein is unable to carry out its normal function. siRNA knockdown of THOC6 revealed increased apoptosis in cultured cells. CONCLUSION: Our findings associate a missense mutation in THOC6 with intellectual disability, suggesting the THO/TREX complex plays an important role in neurodevelopment

Multi-ancestry Mendelian randomization of omics traits revealing drug targets of COVID-19 severity

BACKGROUND: Recent omic studies prioritised several drug targets associated with coronavirus disease 2019 (COVID-19) severity. However, little evidence was provided to systematically estimate the effect of drug targets on COVID-19 severity in multiple ancestries. METHODS: In this study, we applied Mendelian randomization (MR) and colocalization approaches to understand the putative causal effects of 16,059 transcripts and 1608 proteins on COVID-19 severity in European and effects of 610 proteins on COVID-19 severity in African ancestry. We further integrated genetics, clinical and literature evidence to prioritise drug targets. Additional sensitivity analyses including multi-trait colocalization and phenome-wide MR were conducted to test for MR assumptions. FINDINGS: MR and colocalization prioritized four protein targets, FCRL3, ICAM5, ENTPD5 and OAS1 that showed effect on COVID-19 severity in European ancestry. One protein target, SERPINA1 showed a stronger effect in African ancestry but much weaker effect in European ancestry (odds ratio [OR] in Africans=0.369, 95%CI=0.203 to 0.668, P = 9.96 × 10(−4); OR in Europeans=1.021, 95%CI=0.901 to 1.157, P = 0.745), which suggested that increased level of SERPINA1 will reduce COVID-19 risk in African ancestry. One protein, ICAM1 showed suggestive effect on COVID-19 severity in both ancestries (OR in Europeans=1.152, 95%CI=1.063 to 1.249, P = 5.94 × 10(−4); OR in Africans=1.481, 95%CI=1.008 to 2.176; P = 0.045). The OAS1, SERPINA1 and ICAM1 effects were replicated using updated COVID-19 severity data in the two ancestries respectively, where alternative splicing events in OAS1 and ICAM1 also showed marginal effects on COVID-19 severity in Europeans. The phenome-wide MR of the prioritised targets on 622 complex traits provided information on potential beneficial effects on other diseases and suggested little evidence of adverse effects on major complications. INTERPRETATION: Our study identified six proteins as showing putative causal effects on COVID-19 severity. OAS1 and SERPINA1 were targets of existing drugs in trials as potential COVID-19 treatments. ICAM1, ICAM5 and FCRL3 are related to the immune system. Across the six targets, OAS1 has no reliable instrument in African ancestry; SERPINA1, FCRL3, ICAM5 and ENTPD5 showed a different level of putative causal evidence in European and African ancestries, which highlights the importance of more powerful ancestry-specific GWAS and value of multi-ancestry MR in informing the effects of drug targets on COVID-19 across different populations. This study provides a first step towards clinical investigation of beneficial and adverse effects of COVID-19 drug targets. FUNDING: No

Integrative GWAS and co-localisation analysis suggests novel genes associated with age-related multimorbidity

Abstract Advancing age is the greatest risk factor for developing multiple age-related diseases. Therapeutic approaches targeting the underlying pathways of ageing, rather than individual diseases, may be an effective way to treat and prevent age-related morbidity while reducing the burden of polypharmacy. We harness the Open Targets Genetics Portal to perform a systematic analysis of nearly 1,400 genome-wide association studies (GWAS) mapped to 34 age-related diseases and traits, identifying genetic signals that are shared between two or more of these traits. Using locus-to-gene (L2G) mapping, we identify 995 targets with shared genetic links to age-related diseases and traits, which are enriched in mechanisms of ageing and include known ageing and longevity-related genes. Of these 995 genes, 128 are the target of an approved or investigational drug, 526 have experimental evidence of binding pockets or are predicted to be tractable, and 341 have no existing tractability evidence, representing underexplored genes which may reveal novel biological insights and therapeutic opportunities. We present these candidate targets for exploration and prioritisation in a web application

Exome Sequencing as a Diagnostic Tool for Pediatric-Onset Ataxia

Ataxia demonstrates substantial phenotypic and genetic heterogeneity. We set out to determine the diagnostic yield of exome sequencing in pediatric patients with ataxia without a molecular diagnosis after standard-of-care assessment in Canada. FORGE (Finding Of Rare disease GEnes) Canada is a nation-wide project focused on identifying novel disease genes for rare pediatric diseases using whole-exome sequencing. We retrospectively selected all FORGE Canada projects that included cerebellar ataxia as a feature. We identified 28 such families and a molecular diagnosis was made in 13; a success rate of 46%. In 11 families, we identified mutations in genes associated with known neurological syndromes and in two we identified novel disease genes. Exome analysis of sib pairs and/or patients born to consanguineous parents was more likely to be successful (9/13) than simplex cases (4/15). Our data suggest that exome sequencing is an effective first line test for pediatric patients with ataxia where a specific single gene is not immediately suspected to be causative. © 2013 The Authors. *Human Mutation published by Wiley Periodicals, Inc

Mapping interindividual dynamics of innate immune response at single-cell resolution

Common genetic variants across individuals modulate the cellular response to pathogens and are implicated in diverse immune pathologies, yet how they dynamically alter the response upon infection is not well understood. Here, we triggered antiviral responses in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-sequencing. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), a statistical approach designed to identify nonlinear dynamic genetic effects across transcriptional trajectories of cells. This approach identified 1,275 expression quantitative trait loci (local false discovery rate 10%) that manifested during the responses, many of which were colocalized with susceptibility loci identified by genome-wide association studies of infectious and autoimmune diseases, including the OAS1 splicing quantitative trait locus in a COVID-19 susceptibility locus. In summary, our analytical approach provides a unique framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution