Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75–10.05, p = 5.41x10^-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,864 COVID-19 cases (713 with severe and 1,151 with mild disease) and 15,033 ancestry-matched population controls across 4 independent COVID-19 biobanks. We tested whether rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only 1 rare pLOF mutation across these genes among 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We found no evidence of association of rare LOF variants in the 13 candidate genes with severe COVID-19 outcomes.

Rationale: Genetic studies of idiopathic pulmonary fibrosis (IPF) have improved our understanding of this disease, but not all causal loci have been identified. Objectives: To identify genes enriched with rare deleterious variants in IPF and familial pulmonary fibrosis. Methods: We performed gene burden analysis of whole-exome data, tested single variants for disease association, conducted KIF15 (kinesin family member 15) functional studies, and examined human lung single-cell RNA sequencing data. Measurements and Main Results: Gene burden analysis of 1,725 cases and 23,509 control subjects identified heterozygous rare deleterious variants in KIF15, a kinesin involved in spindle separation during mitosis, and three telomere-related genes (TERT [telomerase reverse transcriptase], RTEL1 [regulator of telomere elongation helicase 1], and PARN [poly(A)-specific ribonuclease]). KIF15 was implicated in autosomal-dominant models of rare deleterious variants (odds ratio [OR], 4.9; 95% confidence interval [CI], 2.7–8.8; P = 2.55 × 10⁻⁷) and rare protein-truncating variants (OR, 7.6; 95% CI, 3.3–17.1; P = 8.12 × 10⁻⁷). Meta-analyses of the discovery and replication cohorts, including 2,966 cases and 29,817 control subjects, confirm the involvement of KIF15 plus the three telomere-related genes. A common variant within a KIF15 intron (rs74341405; OR, 1.6; 95% CI, 1.4–1.9; P = 5.63 × 10⁻¹⁰) is associated with IPF risk, confirming a prior report. Lymphoblastoid cells from individuals heterozygous for the common variant have decreased KIF15 and reduced rates of cell growth. Cell proliferation is dependent on KIF15 in the presence of an inhibitor of Eg5/KIF11, which has partially redundant function. KIF15 is expressed specifically in replicating human lung cells and shows diminished expression in replicating epithelial cells of patients with IPF. Conclusions: Both rare deleterious variants and common variants in KIF15 link a nontelomerase pathway of cell proliferation with IPF susceptibility.

Background: Whole genome sequencing (WGS) can detect variants and estimate telomere length. The clinical utility of WGS in estimating risk, progression and survival of pulmonary fibrosis patients is unknown.Methods: In this observational cohort study, we performed WGS on 949 patients with idiopathic pulmonary fibrosis or familial pulmonary fibrosis to determine rare and common variant genotypes, estimate telomere length and assess the association of genomic factors with clinical outcomes.Results: WGS estimates of telomere length correlated with quantitative PCR (R=0.65) and Southern blot (R=0.71) measurements. Rare deleterious qualifying variants were found in 14% of the total cohort, with a five-fold increase in those with a family history of diseaseversusthose without (25%versus5%). Most rare qualifying variants (85%) were found in telomere-related genes and were associated with shorter telomere lengths. Rare qualifying variants had a greater effect on telomere length than a polygenic risk score calculated using 20 common variants previously associated with telomere length. The common variant polygenic risk score predicted telomere length only in sporadic disease. Reduced transplant-free survival was associated with rare qualifying variants, shorter quantitative PCR-measured telomere lengths and absence of theMUC5Bpromoter (rs35705950) single nucleotide polymorphism, but not with WGS-estimated telomere length or the common variant polygenic risk score. Disease progression was associated with both measures of telomere length (quantitative PCR measured and WGS estimated), rare qualifying variants and the common variant polygenic risk score.Conclusion: As a single test, WGS can inform pulmonary fibrosis genetic-mediated risk, evaluate the functional effect of telomere-related variants by estimating telomere length, and prognosticate clinically relevant disease outcomes.

Background: A common approach for sequencing studies is to do joint-calling and store variants of all samples in a single file. If new samples are continually added or controls are re-used for several studies, the cost and time required to perform joint-calling for each analysis can become prohibitive. Results: We present ATAV, an analysis platform for large-scale whole-exome and whole-genome sequencing projects. ATAV stores variant and per site coverage data for all samples in a centralized database, which is efficiently queried by ATAV to support diagnostic analyses for trios and singletons, as well as rare-variant collapsing analyses for finding disease associations in complex diseases. Runtime logs ensure full reproducibility and the modularized ATAV framework makes it extensible to continuous development. Besides helping with the identification of disease-causing variants for a range of diseases, ATAV has also enabled the discovery of disease-genes by rare-variant collapsing on datasets containing more than 20,000 samples. Analyses to date have been performed on data of more than 110,000 individuals demonstrating the scalability of the framework. To allow users to easily access variant-level data directly from the database, we provide a web-based interface, the ATAV data browser (http://atavdb.org/). Through this browser, summary-level data for more than 40,000 samples can be queried by the general public representing a mix of cases and controls of diverse ancestries. Users have access to phenotype categories of variant carriers, as well as predicted ancestry, gender, and quality metrics. In contrast to many other platforms, the data browser is able to show data of newly-added samples in real-time and therefore evolves rapidly as more and more samples are sequenced. Conclusions: Through ATAV, users have public access to one of the largest variant databases for patients sequenced at a tertiary care center and can look up any genes or variants of interest. Additionally, since the entire code is freely available on GitHub, ATAV can easily be deployed by other groups that wish to build their own platform, database, and user interface.