Assessment of community efforts to advance network-based prediction of protein-protein interactions.

Comprehensive understanding of the human protein-protein interaction (PPI) network, aka the human interactome, can provide important insights into the molecular mechanisms of complex biological processes and diseases. Despite the remarkable experimental efforts undertaken to date to determine the structure of the human interactome, many PPIs remain unmapped. Computational approaches, especially network-based methods, can facilitate the identification of previously uncharacterized PPIs. Many such methods have been proposed. Yet, a systematic evaluation of existing network-based methods in predicting PPIs is still lacking. Here, we report community efforts initiated by the International Network Medicine Consortium to benchmark the ability of 26 representative network-based methods to predict PPIs across six different interactomes of four different organisms: A. thaliana, C. elegans, S. cerevisiae, and H. sapiens. Through extensive computational and experimental validations, we found that advanced similarity-based methods, which leverage the underlying network characteristics of PPIs, show superior performance over other general link prediction methods in the interactomes we considered.

Renal Function, Cardiovascular Diseases, Appropriateness of Drug Prescription and Outcomes in Hospitalized Older Patients.

INTRODUCTION: Reduced estimated creatinine clearance (eCrCl) is prevalent in older patients and impacts on drug prescription. In this study, the burden of eCrCl reduction and its associated factors and impact on outcomes were analyzed. Moreover, the rate of inappropriate drug prescription according to eCrCl and its impact on outcomes were described. METHODS: Data were obtained from "REgistro POliterapie SIMI" (REPOSI), a prospective observational register enrolling hospitalized patients aged ≥ 65 years. Patients enrolled from 2010-2016 with available data to calculate eCrCl according to the Cockcroft-Gault formula were included in this analysis. RESULTS: A total of 5046 patients were available for analysis. Among these, we found an eCrCl of 45-59 mL/min in 1163 patients (23.0%), an eCrCl of 30-44 mL/min in 1128 (22.4%), an eCrCl of 15-29 mL/min in 702 (13.9%), and an eCrCl < 15 mL/min in 152 (3.0%), with several clinical factors associated with decreasing eCrCl. During follow-up, a progressively higher risk for all-cause death, cardiovascular (CV) death, any death/re-hospitalization, and CV death/re-hospitalization was found across the renal function classes. Among patients with hypertension, diabetes mellitus, atrial fibrillation, coronary artery disease, and heart failure, 476 (10.9%) were inappropriately prescribed medications according to eCrCl. During follow-up, inappropriate prescription was associated with increased risk of all-cause death (odds ratio [OR] 1.49, 95% confidence interval [CI] 1.13-1.97) and any death/re-hospitalization (OR 1.30, 95% CI 1.03-1.63). CONCLUSIONS: In older hospitalized patients, impaired eCrCl is prevalent and associated with several factors, polypharmacy in particular. Patients with reduced eCrCl have a higher risk of major clinical outcomes, and > 10% of them are prescribed an inappropriate drug, with a higher risk for major clinical outcomes.

Clinical epigenetics settings for cancer and cardiovascular diseases: real-life applications of network medicine at the bedside.

Despite impressive efforts invested in epigenetic research in the last 50 years, clinical applications are still lacking. Only a few university hospital centers currently use epigenetic biomarkers at the bedside. Moreover, the overall concept of precision medicine is not widely recognized in routine medical practice and the reductionist approach remains predominant in treating patients affected by major diseases such as cancer and cardiovascular diseases. By its' very nature, epigenetics is integrative of genetic networks. The study of epigenetic biomarkers has led to the identification of numerous drugs with an increasingly significant role in clinical therapy especially of cancer patients. Here, we provide an overview of clinical epigenetics within the context of network analysis. We illustrate achievements to date and discuss how we can move from traditional medicine into the era of network medicine (NM), where pathway-informed molecular diagnostics will allow treatment selection following the paradigm of precision medicine.

A Case of Pneumocystis jirovecii Pneumonia in a Severely Malnourished, HIV-Negative Patient: A Role for Malnutrition in Opportunistic Infections?

Malnutrition increases the risk of infections in patients receiving medical and surgical procedures, but it is not clear whether it may facilitate also the development of opportunistic infections in human immunodeficiency virus (HIV)-negative patients not receiving immunosuppressive therapies. Here we report the first case of a non-HIV, severely malnourished woman who developed Pneumocystis jirovecii pneumonia. This report highlights the clinical relevance of malnutrition as a determinant of immune suppression, which in turn may also favor opportunistic infections. Therefore, routine nutrition screening and assessment, as well as timely start of nutrition therapy, should be prioritized in daily clinical practice to reduce complications and improve outcome.