From second thoughts on the germ theory to a full-blown host theory

The ouroboros of autoimmunity

Human autoimmunity against elements conferring protective immunity can be symbolized by the 'ouroboros', a snake eating its own tail. Underlying infection is autoimmunity against three immunological targets: neutrophils, complement and cytokines. Autoantibodies against neutrophils can cause peripheral neutropenia underlying mild pyogenic bacterial infections. The pathogenic contribution of autoantibodies against molecules of the complement system is often unclear, but autoantibodies specific for C3 convertase can enhance its activity, lowering complement levels and underlying severe bacterial infections. Autoantibodies neutralizing granulocyte-macrophage colony-stimulating factor impair alveolar macrophages, thereby underlying pulmonary proteinosis and airborne infections, type I interferon viral diseases, type II interferon intra-macrophagic infections, interleukin-6 pyogenic bacterial diseases and interleukin-17A/F mucocutaneous candidiasis. Each of these five cytokine autoantibodies underlies a specific range of infectious diseases, phenocopying infections that occur in patients with the corresponding inborn errors. In this Review, we analyze this ouroboros of immunity against immunity and posit that it should be considered as a factor in patients with unexplained infection.

The germ theory revisited: A noncentric view on infection outcome

The germ theory states that pathogenic microorganisms are responsible for causing infectious diseases. The theory is inherently microbe-centric and does not account for variability in disease severity among individuals and asymptomatic carriership-two phenomena indicating an important role for host variability in infection outcome. The basic tenet of the germ theory was recently challenged, and a radically host-centric paradigm referred to as the "full-blown host theory" was proposed. According to this view, the pathogen is reduced to a passive environmental trigger, and the development of disease is instead due to pre-existing immunodeficiencies of the host. Here, we consider the factors that determine disease severity using established knowledge concerning evolutionary biology, microbial pathogenesis, and host-pathogen interactions. We note that the available data support a noncentric view that recognizes key roles for both the causative microbe and the host in dictating infection outcome.

Human autoantibodies neutralizing type I IFNs: From 1981 to 2023

Human autoantibodies (auto-Abs) neutralizing type I IFNs were first discovered in a woman with disseminated shingles and were described by Ion Gresser from 1981 to 1984. They have since been found in patients with diverse conditions and are even used as a diagnostic criterion in patients with autoimmune polyendocrinopathy syndrome type 1 (APS-1). However, their apparent lack of association with viral diseases, including shingles, led to wide acceptance of the conclusion that they had no pathological consequences. This perception began to change in 2020, when they were found to underlie about 15% of cases of critical COVID-19 pneumonia. They have since been shown to underlie other severe viral diseases, including 5%, 20%, and 40% of cases of critical influenza pneumonia, critical MERS pneumonia, and West Nile virus encephalitis, respectively. They also seem to be associated with shingles in various settings. These auto-Abs are present in all age groups of the general population, but their frequency increases with age to reach at least 5% in the elderly. We estimate that at least 100 million people worldwide carry auto-Abs neutralizing type I IFNs. Here, we briefly review the history of the study of these auto-Abs, focusing particularly on their known causes and consequences.

Quantifying how much host, pathogen, and other factors affect human protective adaptive immune responses

Recognizing the "essential" factors that contribute to a clinical outcome is critical for designing appropriate therapies and prioritizing limited medical resources. Demonstrating a high correlation between a factor and an outcome does not necessarily imply an essential role of the factor to the outcome. Human protective adaptive immune responses to pathogens vary among (and perhaps within) pathogenic strains, human individual hosts, and in response to other factors. Which of these has an "essential" role? We offer three statistical approaches that predict the presence of newly contributing factor(s) and then quantify the influence of host, pathogen, and the new factors on immune responses. We illustrate these approaches using previous data from the protective adaptive immune response (cellular and humoral) by human hosts to various strains of the same pathogenic bacterial species. Taylor's law predicts the existence of other factors potentially contributing to the human protective adaptive immune response in addition to inter-individual host and intra-bacterial species inter-strain variability. A mixed linear model measures the relative contribution of the known variables, individual human hosts and bacterial strains, and estimates the summed contributions of the newly predicted but unknown factors to the combined adaptive immune response. A principal component analysis predicts the presence of sub-variables (currently not defined) within bacterial strains and individuals that may contribute to the combined immune response. These observations have statistical, biological, clinical, and therapeutic implications.

Longitudinal bacterial prevalence in cystic fibrosis airways: Fact and artifact

BACKGROUND

Opportunistic bacterial infection is a hallmark of cystic fibrosis (CF) lung disease and early mortality. Poorly characterized prevalence changes have accompanied two decades of health improvements, with CFTR modulators likely to further affect infection epidemiology.

METHODS

Bacterial prevalence change trends across birth cohorts were assessed with linear regression using 2001-2019 US CF Foundation Patient Registry data. Informative missingness was assessed, as was age-to-age infection status.

RESULTS

Bacterial prevalence constantly changed from 2001 to 2019, with changes differing across birth cohorts. Informative censoring affected prevalence change for some organisms. Age-to-age infection status changes were greater than net changes in bacterial prevalence and varied by age.

CONCLUSIONS

CF infection epidemiology changed over two decades and will continue to do so. Understanding how modulators affect infection epidemiology will require creative designs for longitudinal prevalence change studies emphasizing prevalence changes independent of effects on lung biology.