Associating Genes and Protein Complexes with Disease via Network Propagation

A fundamental challenge in human health is the identification of disease-causing genes. Recently, several studies have tackled this challenge via a network-based approach, motivated by the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein or functional interactions. However, most of these approaches use only local network information in the inference process and are restricted to inferring single gene associations. Here, we provide a global, network-based method for prioritizing disease genes and inferring protein complex associations, which we call PRINCE. The method is based on formulating constraints on the prioritization function that relate to its smoothness over the network and usage of prior information. We exploit this function to predict not only genes but also protein complex associations with a disease of interest. We test our method on gene-disease association data, evaluating both the prioritization achieved and the protein complexes inferred. We show that our method outperforms extant approaches in both tasks. Using data on 1,369 diseases from the OMIM knowledgebase, our method is able (in a cross validation setting) to rank the true causal gene first for 34% of the diseases, and infer 139 disease-related complexes that are highly coherent in terms of the function, expression and conservation of their member proteins. Importantly, we apply our method to study three multi-factorial diseases for which some causal genes have been found already: prostate cancer, alzheimer and type 2 diabetes mellitus. PRINCE''s predictions for these diseases highly match the known literature, suggesting several novel causal genes and protein complexes for further investigation.     

Gene loss rate: a probabilistic measure for the conservation of eukaryotic genes

The rate of conservation of a gene in evolution is believed to be correlated with its biological importance. Recent studies have devised various conservation measures for genes and have shown that they are correlated with several biological characteristics of functional importance. Specifically, the state-of-the-art propensity for gene loss (PGL) measure was shown to be strongly correlated with gene essentiality and its number of protein–protein interactions (PPIs). The observed correlation between conservation and functional importance varies however between conservation measures, underscoring the need for accurate and general measures for the rate of gene conservation. Here we develop a novel maximum-likelihood approach to computing the rate in which a gene is lost in evolution, motivated by the same principles as those underlying PGL. However, in difference to PGL which considers only the most parsimonious ancestral states of the internal nodes of the phylogenetic tree relating the species, our approach weighs in a probabilistic manner all possible ancestral states, and includes the branch length information as part of the probabilistic model. In application to data of 16 eukaryotic genomes, our approach shows higher correlations with experimental data than PGL, including data on gene lethality, level of connectivity in a PPI network and coherence within functionally related genes.     

Vacuolar-type H+-ATPases at the plasma membrane regulate pH and cell migration in microvascular endothelial cells

Microvascular endothelial cells involved in angiogenesis are exposed to an acidic environment that is not conducive for growth and survival. These cells must exhibit a dynamic intracellular (cytosolic) pH (pHcyt) regulatory mechanism to cope with acidosis, in addition to the ubiquitous Na+/H+ exchanger and HCO3--based H+-transporting systems. We hypothesize that the presence of plasmalemmal vacuolar-type proton ATPases (pmV-ATPases) allows microvascular endothelial cells to better cope with this acidic environment and that pmV-ATPases are required for cell migration. This study indicates that microvascular endothelial cells, which are more migratory than macrovascular endothelial cells, express pmV-ATPases. Spectral imaging microscopy indicates a more alkaline pHcyt at the leading than at the lagging edge of microvascular endothelial cells. Treatment of microvascular endothelial cells with V-ATPase inhibitors decreases the proton fluxes via pmV-ATPases and cell migration. These data suggest that pmV-ATPases are essential for pHcyt regulation and cell migration in microvascular endothelial cells.     

Defensive medicine in Israel - a nationwide survey

Background

Defensive medicine is the practice of diagnostic or therapeutic measures conducted primarily as a safeguard against possible malpractice liability. We studied the extent, reasons, and characteristics of defensive medicine in the Israeli health care system.

Methods and Findings

Cross-sectional study performed in the Israeli health care system between April and July 2008 in a sample (7%) of board certified physicians from eight medical disciplines (internal medicine, pediatrics, general surgery, family medicine, obstetrics and gynecology, orthopedic surgery, cardiology, and neurosurgery). A total of 889 physicians (7% of all Israeli board certified specialists) completed the survey. The majority [60%, (95%CI 0·57–0·63)] reported practicing defensive medicine; 40% (95%CI 0·37–0·43) consider every patient as a potential threat for a medical lawsuit; 25% (95%CI 0·22–0·28) have previously been sued at least once during their career. Independent predictors for practicing defensive medicine were surgical specialty [OR = 1.6 (95%CI 1·2–2·2), p = 0·0004], not performing a fellowship abroad [OR = 1·5 (95%CI 1·1–2), p = 0·027], and previous exposure to lawsuits [OR = 2·4 (95%CI 1·7–3·4), p<0·0001]. Independent predictors for the risk of being sued during a physician''s career were male gender [OR = 1·6 (95%CI 1·1–2·2), p = 0·012] and surgery specialty [OR = 3·2 (95%CI 2·4–4·3), p<0·0001] (general surgery, obstetrics and gynecology, orthopedic surgery, and neurosurgery).

Conclusions

Defensive medicine is very prevalent in daily physician practice in all medical disciplines. It exposes patients to complications due to unnecessary tests and procedures, affects quality of care and costs, and undermines doctor-patient relationships. Further studies are needed to understand how to minimize defensive medicine resulting from an increased malpractice liability market.     

Prediction of microbial growth rate versus biomass yield by a metabolic network with kinetic parameters

Identifying the factors that determine microbial growth rate under various environmental and genetic conditions is a major challenge of systems biology. While current genome-scale metabolic modeling approaches enable us to successfully predict a variety of metabolic phenotypes, including maximal biomass yield, the prediction of actual growth rate is a long standing goal. This gap stems from strictly relying on data regarding reaction stoichiometry and directionality, without accounting for enzyme kinetic considerations. Here we present a novel metabolic network-based approach, MetabOlic Modeling with ENzyme kineTics (MOMENT), which predicts metabolic flux rate and growth rate by utilizing prior data on enzyme turnover rates and enzyme molecular weights, without requiring measurements of nutrient uptake rates. The method is based on an identified design principle of metabolism in which enzymes catalyzing high flux reactions across different media tend to be more efficient in terms of having higher turnover numbers. Extending upon previous attempts to utilize kinetic data in genome-scale metabolic modeling, our approach takes into account the requirement for specific enzyme concentrations for catalyzing predicted metabolic flux rates, considering isozymes, protein complexes, and multi-functional enzymes. MOMENT is shown to significantly improve the prediction accuracy of various metabolic phenotypes in E. coli, including intracellular flux rates and changes in gene expression levels under different growth rates. Most importantly, MOMENT is shown to predict growth rates of E. coli under a diverse set of media that are correlated with experimental measurements, markedly improving upon existing state-of-the art stoichiometric modeling approaches. These results support the view that a physiological bound on cellular enzyme concentrations is a key factor that determines microbial growth rate.     

Micropropagation of Achillea filipendulina cv. ‘Parker’

Achillea filipendulina (family Asteraceae) is widespread throughout temperate North America. In order to clean stock plants from endemic fungal and bacterial contaminations a method for large-scale propagation of A. filipendulina through meristem culture was sought and found and is described in this paper. The best conditions for propagating A. filipendulina was found to be MS (Murashige and Skoog) salt medium supplemented with 3% sucrose and 1 mg l^–1 IAA (indole-3-acetic acid) plus 2 mg l^–1 BA (6-benzyladenine) under 16 h of cool fluorescent light. Rooted plants were successfully acclimatized within a short time after propagating on this medium. The propagation via tissue culture did not affect plant's presentation. The use of clean stock plants made it possible to increased Israeli production of Achillea from about 150,000 stems a year to about 1,300,000 stems a year.     

Type-II Myocardial Infarction – Patient Characteristics,Management and Outcomes

Background

Type-II MI is defined as myocardial infarction (MI) secondary to ischemia due to either increased oxygen demand or decreased supply. This categorization has been used for the last five years, yet, little is known about patient characteristics and clinical outcomes. In the current work we assessed the epidemiology, causes, management and outcomes of type II MI patients.

Methods

A comparative analysis was performed between patients with type-I and type-II MI who participated in two prospective national Acute Coronary Syndrome Israeli Surveys (ACSIS) performed in 2008 and 2010.

Results

The surveys included 2818 patients with acute MI of whom 127 (4.5%) had type-II MI. The main causes of type-II MI were anemia (31%), sepsis (24%), and arrhythmia (17%). Patients with type-II MI tended to be older (75.6±12 vs. 63.8±13, p<0.0001), female majority (43.3% vs. 22.3%, p<0.0001), had more frequently impaired functional level (45.7% vs. 17%, p<0.0001) and a higher GRACE risk score (150±32 vs. 110±35, p<0.0001). Patients with type-II MI were significantly less often referred for coronary interventions (36% vs. 89%, p<0.0001) and less frequently prescribed guideline-directed medical therapy. Mortality rates were substantially higher among patients with type-II MI both at thirty-day (13.6% vs. 4.9%, p<0.0001) and at one-year (23.9% vs. 8.6%, p<0.0001) follow-ups.

Conclusions

Patients with type-II compared to type-I MI have distinct demographics, increased prevalence of multiple comorbidities, a high-risk cardiovascular profile and an overall worse outcome. The complex medical condition of this cohort imposes a great therapeutic challenge and specific guidelines with recommended medical treatment and invasive strategies are warranted.