Elucidation of disease etiology by trans-layer omics analysis

To date, genome-wide association studies (GWASs) have successfully identified thousands of associations between genetic polymorphisms and human traits. However, the pathways between the associated genotype and phenotype are often poorly understood. The transcriptome, proteome, and metabolome, the omics, are positioned along the pathway and can provide useful information to translate from genotype to phenotype. This review shows useful data resources for connecting each omics and describes how they are combined into a cohesive analysis. Quantitative trait loci (QTL) are useful information for connecting the genome and other omics. QTL represent how much genetic variants have effects on other omics and give us clues to how GWAS risk SNPs affect biological mechanisms. Integration of each omics provides a robust analytical framework for estimating disease causality, discovering drug targets, and identifying disease-associated tissues. Technological advances and the rise of consortia and biobanks have facilitated the analyses of unprecedented data, improving both the quality and quantity of research. Proficient management of these valuable datasets allows discovering novel insights into the genetic background and etiology of complex human diseases and contributing to personalized medicine.

Evaluation of Disease Causality of Rare Ixodes ricinus-Borne Infections in Europe

In Europe, Ixodes ricinus ticks transmit pathogens such as Borrelia burgdorferi sensu lato and tick-borne encephalitis virus (TBEV). In addition, there is evidence for transmission to humans from I. ricinus of Anaplasma phagocytophilum, Babesia divergens, Babesia microti, Babesia venatorum, Borrelia miyamotoi, Neoehrlichia mikurensis, Rickettsia helvetica and Rickettsia monacensis. However, whether infection with these potential tick-borne pathogens results in human disease has not been fully demonstrated for all of these tick-borne microorganisms. To evaluate the available evidence for a causative relation between infection and disease, the current study analyses European case reports published from 2008 to 2018, supplemented with information derived from epidemiological and experimental studies. The evidence for human disease causality in Europe found in this review appeared to be strongest for A. phagocytophilum and B. divergens. Nonetheless, some knowledge gaps still exist. Importantly, comprehensive evidence for pathogenicity is lacking for the remaining tick-borne microorganisms. Such evidence could be gathered best through prospective studies, for example, studies enrolling patients with a fever after a tick bite, the development of specific new serological tools, isolation of these microorganisms from ticks and patients and propagation in vitro, and through experimental studies.

Begutachtung von Berufskrankheiten am Beispiel pneumologischer Erkrankungen

Orders for medical expertise reports of the accident insurance institutions and the social courts often have very difficult and complex issues and therefore require a high level of medical expertise as well as occupational health and accident insurance law knowledge. This applies in particular to the expert opinion as to whether a causal connection exists between occupational effects and the disease. Causality must be described on the basis of the current state of medical and scientific knowledge in such a way that it is comprehensible for an accident insurance institution or for a court. The insured person himself should also be able to comprehensively understand the content of the opinion and its consequences.

High Throughput Sequencing For Plant Virus Detection and Discovery

Over the last decade, virologists have discovered an unprecedented number of viruses using high throughput sequencing (HTS), which led to the advancement of our knowledge on the diversity of viruses in nature, particularly unraveling the virome of many agricultural crops. However, these new virus discoveries have often widened the gaps in our understanding of virus biology; the forefront of which is the actual role of a new virus in disease, if any. Yet, when used critically in etiological studies, HTS is a powerful tool to establish disease causality between the virus and its host. Conversely, with globalization, movement of plant material is increasingly more common and often a point of dispute between countries. HTS could potentially resolve these issues given its capacity to detect and discover. Although many pipelines are available for plant virus discovery, all share a common backbone. A description of the process of plant virus detection and discovery from HTS data are presented, providing a summary of the different pipelines available for scientists’ utility in their research.

What Is a Host? Attributes of Individual Susceptibility

ABSTRACTIn every epidemic some individuals become sick and some may die, whereas others recover from illness and still others show no signs or symptoms of disease. These differences highlight a fundamental question of microbial pathogenesis: why are some individuals susceptible to infectious diseases while others who acquire the same microbe remain well? For most of human history, the answer assumed the hand of providence. With the advent of the germ theory of disease, the focus on disease causality became the microbe, but this did not explain how there can be different outcomes of infection in different individuals with the same microbe. Here we examine the attributes of susceptibility in the context of the “damage-response framework” of microbial pathogenesis. We identify 11 attributes that, although not independent, are sufficiently distinct to be considered separately: microbiome, inoculum, sex, temperature, environment, age, chance, history, immunity, nutrition, and genetics. We use the first letter of each to create the mnemonic MISTEACHING, underscoring the need for caution in accepting dogma and attributing disease causality to any single factor. For both populations and individuals, variations in the attributes that assemble into MISTEACHING can create an enormity of combinations that can in turn translate into different outcomes of host-microbe encounters. Combinatorial diversity among the 11 attributes makes identifying “signatures” of susceptibility possible. However, with their inevitable uncertainties and propensity to change, there may still be a low likelihood for prediction with regard to individual host-microbe interactions, although probabilistic prediction may be possible.