Genetic Predisposition and the Variable Course of Infectious Diseases.

BACKGROUND: Contact with a pathogen is followed by variable courses of infectious disease, which are only partly explicable by classical risk factors. The susceptibility to infection is variable, as is the course of disease after infection. In this review, we discuss the extent to which this variation is due to genetic factors of the affected individual (the host). METHODS: Selective review of the literature on host genetics in infectious disease, with special attention to the pathogens SARSCoV- 2, influenza viruses, Mycobacterium tuberculosis, and human immunodeficiency virus (HIV). RESULTS: Genetic variants of the host contribute to the pathogenesis of infectious diseases. For example, in HIV infection, a relatively common variant leading to a loss of function of the HIV co-receptor CCR5 affects the course of the disease, as do variants in genes of the major histocompatibility complex (MHC) region. Rare monogenic variants of the interferon immune response system contribute to severe disease courses in COVID-19 and influenza (type I interferon in these two cases) and in tuberculosis (type II interferon). An estimated 1.8% of life-threatening courses of COVID-19 in men under age 60 are caused by a deficiency of toll-like receptor 7. The scientific understanding of host genetic factors has already been beneficial to the development of effective drugs. In a small number of cases, genetic information has also been used for individual therapeutic decision-making and for the identification of persons at elevated risk. CONCLUSION: A comprehensive understanding of host genetics can improve the care of patients with infectious diseases. Until the present, the clinical utility of host genetics has been limited to rare cases; in the future, polygenic risk scores summarizing the relevant genetic variants in each patient will enable a wider benefit. To make this possible, multicenter studies are needed that will systematically integrate clinical and genetic data.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity.

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality.

BackgroundThere is considerable variability in COVID-19 outcomes among younger adults, and some of this variation may be due to genetic predisposition.MethodsWe combined individual level data from 13,888 COVID-19 patients (n = 7185 hospitalized) from 17 cohorts in 9 countries to assess the association of the major common COVID-19 genetic risk factor (chromosome 3 locus tagged by rs10490770) with mortality, COVID-19-related complications, and laboratory values. We next performed metaanalyses using FinnGen and the Columbia University COVID-19 Biobank.ResultsWe found that rs10490770 risk allele carriers experienced an increased risk of all-cause mortality (HR, 1.4; 95% CI, 1.2-1.7). Risk allele carriers had increased odds of several COVID-19 complications: severe respiratory failure (OR, 2.1; 95% CI, 1.6-2.6), venous thromboembolism (OR, 1.7; 95% CI, 1.2-2.4), and hepatic injury (OR, 1.5; 95% CI, 1.2-2.0). Risk allele carriers age 60 years and younger had higher odds of death or severe respiratory failure (OR, 2.7; 95% CI, 1.8-3.9) compared with those of more than 60 years (OR, 1.5; 95% CI, 1.2-1.8; interaction, P = 0.038). Among individuals 60 years and younger who died or experienced severe respiratory failure, 32.3% were risk-variant carriers compared with 13.9% of those not experiencing these outcomes. This risk variant improved the prediction of death or severe respiratory failure similarly to, or better than, most established clinical risk factors.ConclusionsThe major common COVID-19 genetic risk factor is associated with increased risks of morbidity and mortality, which are more pronounced among individuals 60 years or younger. The effect was similar in magnitude and more common than most established clinical risk factors, suggesting potential implications for future clinical risk management.

TBK1 and TNFRSF13B mutations and an autoinflammatory disease in a child with lethal COVID-19.

Among children, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are typically mild. Here, we describe the case of a 3.5-year-old girl with an unusually severe presentation of coronavirus disease (COVID-19). The child had an autoinflammatory disorder of unknown etiology, which had been treated using prednisolone and methotrexate, and her parents were half cousins of Turkish descent. After 5 days of nonspecific viral infection symptoms, tonic-clonic seizures occurred followed by acute cardiac insufficiency, multi-organ insufficiency, and ultimate death. Trio exome sequencing identified a homozygous splice-variant in the gene TBK1, and a homozygous missense variant in the gene TNFRSF13B. Heterozygous deleterious variants in the TBK1 gene have been associated with severe COVID-19, and the variant in the TNFRSF13B gene has been associated with common variable immunodeficiency (CVID). We suggest that the identified variants, the autoinflammatory disorder and its treatment, or a combination of these factors probably predisposed to lethal COVID-19 in the present case.

LAMP-Seq enables sensitive, multiplexed COVID-19 diagnostics using molecular barcoding.

Frequent testing of large population groups combined with contact tracing and isolation measures will be crucial for containing Coronavirus Disease 2019 outbreaks. Here we present LAMP-Seq, a modified, highly scalable reverse transcription loop-mediated isothermal amplification (RT-LAMP) method. Unpurified biosamples are barcoded and amplified in a single heat step, and pooled products are analyzed en masse by sequencing. Using commercial reagents, LAMP-Seq has a limit of detection of ~2.2 molecules per µl at 95% confidence and near-perfect specificity for severe acute respiratory syndrome coronavirus 2 given its sequence readout. Clinical validation of an open-source protocol with 676 swab samples, 98 of which were deemed positive by standard RT-qPCR, demonstrated 100% sensitivity in individuals with cycle threshold values of up to 33 and a specificity of 99.7%, at a very low material cost. With a time-to-result of fewer than 24 h, low cost and little new infrastructure requirement, LAMP-Seq can be readily deployed for frequent testing as part of an integrated public health surveillance program.

Structure-guided multivalent nanobodies block SARS-CoV-2 infection and suppress mutational escape.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to spread, with devastating consequences. For passive immunization efforts, nanobodies have size and cost advantages over conventional antibodies. In this study, we generated four neutralizing nanobodies that target the receptor binding domain of the SARS-CoV-2 spike protein. We used x-ray crystallography and cryo-electron microscopy to define two distinct binding epitopes. On the basis of these structures, we engineered multivalent nanobodies with more than 100 times the neutralizing activity of monovalent nanobodies. Biparatopic nanobody fusions suppressed the emergence of escape mutants. Several nanobody constructs neutralized through receptor binding competition, whereas other monovalent and biparatopic nanobodies triggered aberrant activation of the spike fusion machinery. These premature conformational changes in the spike protein forestalled productive fusion and rendered the virions noninfectious.