Relevance of pepsinogen, gastrin, and endoscopic atrophy in the diagnosis of autoimmune gastritis

Simple objective modalities are required for evaluating suspected autoimmune gastritis (AIG). This cross-sectional study aimed to examine whether pepsinogen, gastrin, and endoscopic findings can predict AIG. The diagnostic performance of endoscopic findings and serology in distinguishing AIG was evaluated. AIG was diagnosed in patients (N = 31) with anti-parietal cell antibody and/or intrinsic factor antibody positivity and histological findings consistent with AIG. Non-AIG patients (N = 301) were seronegative for anti-parietal cell antibodies. Receiver operating characteristic curve analysis of the entire cohort (N = 332) identified an endoscopic atrophic grade cutoff point of O3 on the Kimura–Takemoto classification (area under the curve [AUC]: 0.909), while those of pepsinogen-I, I/II ratio, and gastrin were 20.1 ng/mL (AUC: 0.932), 1.8 (AUC: 0.913), and 355 pg/mL (AUC: 0.912), respectively. In severe atrophy cases (≥ O3, N = 58, AIG/control; 27/31), the cutoff values of pepsinogen-I, I/II ratio, and gastrin were 9.8 ng/mL (AUC: 0.895), 1.8 (AUC: 0.86), and 355 pg/mL (AUC: 0.897), respectively. In conclusion, endoscopic atrophy is a predictor of AIG. High serum gastrin and low pepsinogen-I and I/II ratio are predictors even in the case of severe atrophy, suggesting their usefulness when the diagnosis of AIG is difficult or as serological screening tests

Understanding diabetes in patients with HIV/AIDS

This paper reviews the incidence, pathogenetic mechanisms and management strategies of diabetes mellitus in patients with human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS). It classifies patients based on the aetiopathogenetic mechanisms, and proposes rational methods of management of the condition, based on aetiopathogenesis and concomitant pharmacotherapy

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.Comment: 49 pages, 2 figures, 2 tables, 10 supplementary figures, 13 supplementary table

Drug-target network in myocardial infarction reveals multiple side effects of unrelated drugs

The systems-level characterization of drug-target associations in myocardial infarction (MI) has not been reported to date. We report a computational approach that combines different sources of drug and protein interaction information to assemble the myocardial infarction drug-target interactome network (My-DTome). My-DTome comprises approved and other drugs interlinked in a single, highly-connected network with modular organization. We show that approved and other drugs may both be highly connected and represent network bottlenecks. This highlights influential roles for such drugs on seemingly unrelated targets and pathways via direct and indirect interactions. My-DTome modules are associated with relevant molecular processes and pathways. We find evidence that these modules may be regulated by microRNAs with potential therapeutic roles in MI. Different drugs can jointly impact a module. We provide systemic insights into cardiovascular effects of non-cardiovascular drugs. My-DTome provides the basis for an alternative approach to investigate new targets and multidrug treatment in MI