The genetics underlying severe COVID-19: The immune system is complex and involves many genes, including those that encode cytokines known as interferons (IFNs). Individuals that lack specific IFNs can be more susceptible to infectious diseases. Furthermore, the autoantibody system dampens IFN response to prevent damage from pathogen-induced inflammation. Two studies now examine the likelihood that genetics affects the risk of severe coronavirus disease 2019 (COVID-19) through components of this system (see the Perspective by Beck and Aksentijevich). Q. Zhang et al. used a candidate gene approach and identified patients with severe COVID-19 who have mutations in genes involved in the regulation of type I and III IFN immunity. They found enrichment of these genes in patients and conclude that genetics may determine the clinical course of the infection. Bastard et al. identified individuals with high titers of neutralizing autoantibodies against type I IFN-α2 and IFN-ω in about 10% of patients with severe COVID-19 pneumonia. These autoantibodies were not found either in infected people who were asymptomatic or had milder phenotype or in healthy individuals. Together, these studies identify a means by which individuals at highest risk of life-threatening COVID-19 can be identified. Science , this issue p. eabd4570 , p. eabd4585 ; see also p. 404

Understanding the longevity of antibodies against SARS-CoV-2 infection is of utmost importance in predicting the further course of the pandemic and to plan vaccination strategies. Here we report a ...

Background: SARS-CoV-2 infection can lead to persistent or newly emerging symptoms lasting for months, a condition known as long COVID (LC). The pathophysiology of LC remains poorly understood, with cytokine dysregulation proposed as a key mechanism, although findings across the studies have been inconsistent. Patients and methods: We conducted a longitudinal study using the Olink^® Target 96 Inflammation Panel to assess cytokines in COVID-19 (COV) patients at three months and six months post-infection. These profiles were compared with those of individuals recovering from other upper respiratory tract infections (non-COV). Additionally, we analyzed differences between individuals with LC and those who recovered from COVID-19. Predictive models for LC at three months and sixth months post-infection were developed using inflammatory markers and relevant clinical cofactors, including gender, age, BMI, hemogram, Β2-microglobulin, D-dimers, LDH, AST, ALT, Ferritin, vitamin D, CRP, and the severity of acute COVID-19 infection as classified by WHO criteria. Results: We observed a general decline in inflammatory biomarkers in post-COVID-19 patients over time, with only a few cytokines elevated (CCL4 at month 3 and CST5 at month 6) compared to non-COV controls. In LC patients, an early phase of low-grade inflammation transitioned into significant reduction in proinflammatory biomarkers compared to recovered individuals. Rather than indicating immune normalization, this pattern suggests a possible suppression or exhaustion of the immune response in the months following acute infection. Importantly, our predictive modeling demonstrated that this specific cytokine signature, in combination with acute disease severity and clinical cofactors, described well the presence of LC. Conclusions: Our findings suggest that inflammation-related biomarker dysregulation following acute SARS-CoV-2 infection evolves dynamically over a six-month period. By the sixth month, compared to the third month, the presence of LC is more accurately predicted by a combination of persistent biomarker alteration and the severity of the initial infection, as defined by WHO criteria. This represents a novel insight, as previous studies have primarily associated LC with elevated proinflammatory markers, whereas our results suggest that immune suppression or exhaustion may play a more prominent role in the later stages.