ARDD 2020: from aging mechanisms to interventions

Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead to novel discoveries to treat age-related diseases. The present review summarizes presentations from the 7th Annual Aging Research and Drug Discovery (ARDD) meeting, held online on the 1st to 4th of September 2020. The meeting covered topics related to new methodologies to study aging, knowledge about basic mechanisms of longevity, latest interventional strategies to target the aging process as well as discussions about the impact of aging research on society and economy. More than 2000 participants and 65 speakers joined the meeting and we already look forward to an even larger meeting next year. Please mark your calendars for the 8th ARDD meeting that is scheduled for the 31st of August to 3rd of September, 2021, at Columbia University, USA

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

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 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

IT Innovation Squeeze: Propositions and a Methodology for Deciding to Continue or Decommission Legacy Systems

Part 6: Theory and MethodsInternational audienceOrganizations have been confronted with fast moving developments in the Information Technology (IT) sector over the past decades. Many new technological paradigms have emerged and left a landscape of legacy in which more and more money is spent on maintaining this landscape at the expense of innovating. Especially where business requirements put time pressure on the evolution of the IT landscape the decision whether to continue and maintain legacy systems or to decommission legacy systems in time has become a huge challenge. We formulate a set of propositions influencing the decision to decommission or continue legacy systems. This set of propositions is derived from literature and interviews with high level managers of organizations. Software characteristics, development methods, dependency of systems, lock-in, system complexity, new technologies and system ownership influence the decision whether to decommission or to maintain a system. We conclude this paper by proposing a methodology that helps organizations in finding the right balance between discontinuing and maintaining legacy systems

Alzheimer's disease and symbiotic microbiota: an evolutionary medicine perspective

Microorganisms resident in our bodies participate in a variety of regulatory and pathogenic processes. Here, we describe how etiological pathways implicated in Alzheimer’s disease (AD) may be regulated or disturbed by symbiotic microbial activity. Furthermore, the composition of symbiotic microbes has changed dramatically across human history alongside the rise of agriculturalism, industrialization, and globalization. We postulate that each of these lifestyle transitions engendered progressive depletion of microbial diversity and enhancement of virulence, thereby enhancing AD risk pathways. It is likely that the human life span extended into the eighth decade tens of thousands of years ago, yet little is known about premodern geriatric epidemiology. We propose that microbiota of the gut, oral cavity, nasal cavity, and brain may modulate AD pathogenesis, and that changes in the microbial composition of these body regions across history suggest escalation of AD risk. Dysbiosis may promote immunoregulatory dysfunction due to inadequate education of the immune system, chronic inflammation, and epithelial barrier permeability. Subsequently, proinflammatory agents—and occasionally microbes—may infiltrate the brain and promote AD pathogenic processes. APOE genotypes appear to moderate the effect of dysbiosis on AD risk. Elucidating the effect of symbiotic microbiota on AD pathogenesis could contribute to basic and translational research

Erratum: Gaia Data Release 2: Kinematics of globular clusters and dwarf galaxies around the Milky Way (A&A (2018) 616 (A12) DOI: 10.1051/0004-6361/201832698)

An error occurred during the production process of the original published version. The following names were omitted from the author list: R. Haigron, D. Hatzidimitriou, M. Hauser, M. Haywood, U. Heiter, J. Heu, T. Hilger. The original published version has been corrected together with the publication of this corrigendum. © 2020 EDP Sciences. All rights reserved