Showing papers by "Katherine S. Elliott published in 2022"

Whole-genome sequencing reveals host factors underlying critical COVID-19

Abstract: Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2-4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.

Human Leukocyte Antigen Association Study Reveals DRB1*04:02 Effects Additional to DRB1*07:01 in Anti-LGI1 Encephalitis

Abstract: Background and Objectives To study human leukocyte antigen (HLA) allele associations in anti-leucine–rich glioma-inactivated 1 (LGI1) encephalitis. Methods A multiethnic cohort of 269 patients with anti-LGI1 encephalitis and 1,359 controls was included. Four-digit HLA sequencing and genome wide association single-nucleotide polymorphism typing imputation (0.99 concordance) were used for HLA typing. Significance of primary and secondary associations was tested using χ2, Fisher exact tests, or logistic regression with the control of population stratification covariates when applicable. Results DRB1*07:01 and DQA1*02:01, 2 alleles in strong linkage disequilibrium, were associated with the disease (90% vs 24%, OR = 27.8, p < 10e−50) across ethnicity independent of variation at DRB3 and DQB1, 2 flanking HLA loci. DRB1*07:01 homozygosity was associated with a doubling of risk (OR = 2.1, p = 0.010), suggesting causality. DRB1*07:01 negative subjects were younger (p = 0.003) and more frequently female (p = 0.015). Three patients with malignant thymomas did not carry DRB1*07:01, whereas patients with other tumors had high DRB1*07:01 frequency, suggesting that the presence of tumors other than thymomas may be coincidental and not causal. In both DRB1*07:01 heterozygous individuals and DRB1*07:01 negative subjects, DRB1*04:02 was associated with anti-LGI1 encephalitis, indicating an independent effect of this allele (OR = 6.85, p = 4.57 × 10−6 and OR = 8.93, p = 2.50 × 10−3, respectively). DRB1*04:02 was also independently associated with younger age at onset (β = −6.68, p = 9.78 × 10−3). Major histocompatibility complex peptide-binding predictions using LGI1-derived peptides revealed divergent binding propensities for DRB1*04:02 and DRB1*07:01 alleles, suggesting independent pathogenic mechanisms. Discussion In addition to the established primary DRB1*07:01 association in anti-LGI1 encephalitis, we observe a secondary effect of DRB1*04:02 with lower age at onset. Our study provides evidence for secondary effects within HLA locus that correlate with clinical phenotypes in anti-LGI1 encephalitis.

036 A GWAS of LGI1-antibody encephalitis

Abstract: Introduction Patients with encephalitis with antibodies to leucine-rich glioma-inactivated 1 (LGI1-Ab-E) are typically elderly males with a distinct phenotype, and ~90% carry the class II major histocompatibility (MHC) allele, DRB1*07:01. This allele is found in ~25% of healthy controls, suggesting other genetic and environmental disease factors operate in patients with LGI1-Ab-E. Yet, a previous genome-wide associa- tion study did not find variants attaining genome-wide significance outside the MHC region. Methods LGI1-Ab-E patients were genome-wide genotyped with standard arrays. Missing variants were imputed using Minimac4 and the Haplotype Reference Consortium panel. Population-matched controls were selected from UK Biobank. Genetic association with LGI1-Ab-E was determined with PLINK, SNPTEST and GWAMA and processed using bespoke bioinformatics pipelines. The discovery cohort of 131 French patients (92 men; 70%) was population-matched with 2613 controls (957 men; 36.6%): >6 million SNPs remained after quality control (lambda 1.04). The validation cohort comprises 97 US/UK cases (66 men; 68%) and 1940 matched controls (882 men; 45%), >5 million variants and lambda of 1. Results We replicated the MHC association (rs2858869, p=3.371e-52 in the discovery cohort; rs2858870, p=1.085e-54 in the validation cohort) and will report the extent of non-MHC associations currently under- going bioinformatic assessment and validation.

Fine-Scale Genetic Structure in the United Arab Emirates Reflects Endogamous and Consanguineous Culture, Population History, and Geography

Abstract: Abstract The indigenous population of the United Arab Emirates (UAE) has a unique demographic and cultural history. Its tradition of endogamy and consanguinity is expected to produce genetic homogeneity and partitioning of gene pools while population movements and intercontinental trade are likely to have contributed to genetic diversity. Emiratis and neighboring populations of the Middle East have been underrepresented in the population genetics literature with few studies covering the broader genetic history of the Arabian Peninsula. Here, we genotyped 1,198 individuals from the seven Emirates using 1.7 million markers and by employing haplotype-based algorithms and admixture analyses, we reveal the fine-scale genetic structure of the Emirati population. Shared ancestry and gene flow with neighboring populations display their unique geographic position while increased intra- versus inter-Emirati kinship and sharing of uniparental haplogroups, reflect the endogamous and consanguineous cultural traditions of the Emirates and their tribes.

Title: Fine-scale genetic structure in the United Arab Emirates reflects endogamous and consanguineous culture, population history and geography

Abstract: The indigenous population of the United Arab Emirates (UAE) has a unique demographic and cultural history. Its tradition of endogamy and consanguinity is expected to produce genetic homogeneity and partitioning of gene pools while population movements and intercontinental trade are likely to have contributed to genetic diversity. Emiratis and neighbouring populations of the Middle East have been underrepresented in the population genetics literature with few studies covering the broader genetic history of the Arabian Peninsula. Here, we genotyped 1,198 individuals from the seven Emirates using 1.7 million markers and by employing haplotype-based algorithms and admixture analyses we reveal the fine-scale genetic structure of the Emirati population. Shared ancestry and gene flow with neighbouring populations display their unique geographic position while increased intra- vs inter-Emirati kinship and sharing of uniparental haplogroups, reflect the endogamous and consanguineous cultural traditions of the Emirates and their tribes.

Leveraging genetic correlation across immune-mediated disease to gain insights into underpowered studies of rare conditions

Abstract: Prevalence of immune mediated disease (IMD) within N. European populations varies from common (atopic dermatitis AD=10%) to rarer (giant cell arteritis-GCA=0.02%; hidradenitis suppurativa-HS=0.77%). This directly affects statistical power to detect genomewide SNP associations and to identify “causal” genes. Leverage genetic correlations between differently powered IMD cohorts to study the genetic mechanisms underlying multiple immune-mediated diseases. We used UK Biobank clinical data to create 18 IMD cohorts and a control set of individuals without any history of autoimmune disease (N=50,136). Using whole genome sequencing data from ~140K participants of the UKB, we performed SNP-level GWAS with REGENIE v2, and prioritized the associated genes using association statistics, in silico annotation, and eQTL information, as implemented in the Priority Index (Pi) algorithm. We used k-means clustering across relative gene rank distances optimized with the elbow method to group IMDs according to similar genetic architectures. IMD cohort size ranged from 196 to 3,411 cases and were each compared with a common set of controls. Optimal clustering yielded 4 groups, each with 6,5,4 or 3 IMD’s respectively. One cluster of interest contained HS, AD, vitiligo, GCA and Sjogren’s syndrome. This cluster reflects similarity in common “pathogenic” genes across IMD and highlights new candidate genes for further investigation that would otherwise go unnoticed in poorly powered studies of GCA and HS. In conclusion, our proposed use of genetic associations and clustering of their relative ranks across multiple disease phenotypes identified pathogenic genes in understudied IMDs that would otherwise not have been elucidated. Supported by Janssen Research & Development

Whole genome sequencing reveals host factors underlying critical Covid-19 Accelerated Article Preview

Abstract: Critical Covid-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care 1 or hospitalisation 2–4 following SARS-CoV-2 infection. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from critically-ill cases with population controls in order to find underlying disease mechanisms. Here, we use whole genome sequencing in 7,491 critically-ill cases compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical Covid-19. We identify 16 new independent associations, including variants within genes involved in interferon signalling ( IL10RB , PLSCR1 ), leucocyte differentiation ( BCL11A ), and blood type antigen secretor status ( FUT2 ). Using transcriptome-wide association and colocalisation to infer the effect of gene expression on disease severity, we find evidence implicating multiple genes, including reduced expression of a membrane flippase ( ATP11A ), and increased mucin expression ( MUC1 ), in critical disease. Mendelian randomisation provides evidence in support of causal roles for myeloid cell adhesion molecules ( SELE , ICAM5 , CD209 ) and coagulation factor F8 , all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of Covid-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication, or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between critically-ill cases and population controls is highly efficient for detection of therapeutically-relevant mechanisms of disease.