The interactive role of type 2 diabetes mellitus and E-selectin S128R mutation on susceptibility to coronary heart disease

<p>Abstract</p> <p>Background</p> <p>The role of gene-environment interactions as risk factors for coronary heart disease (CAD) remains largely undefined. Such interactions may involve gene mutations and disease conditions such as type 2 diabetes mellitus (DM2) predisposing individuals to acquiring the disease.</p> <p>Methods</p> <p>In the present study, we assessed the possible interactive effect of DM2 and E-selectin S128R polymorphism with respect to its predisposing individuals to CAD, using as a study model a population of 1,112 patients and 427 angiographed controls of Saudi origin. E-selectin genotyping was accomplished by polymerase chain reaction (PCR) amplification followed by <it>Pst</it>I restriction enzyme digestion.</p> <p>Results</p> <p>The results show that DM2 is an independent risk factor for CAD. In the absence of DM2, the presence of the R mutant allele alone is not significantly associated with CAD (p = 0.431, OR 1.28). In contrast, in the presence of DM2 and the S allele, the likelihood of an individual acquiring CAD is significant (odds ratio = 5.44; p = < 0.001). This effect of DM2 becomes remarkably greater in the presence of the mutant 128R allele, as can be observed from the odds ratio of their interaction term (odds ratio = 6.11; p = < 0.001).</p> <p>Conclusion</p> <p>Our findings indicate therefore that the risk of acquiring CAD in patients with DM2 increases significantly in the presence of the 128R mutant allele of the E-selectin gene.</p

Salicylic acid and salicylic acid glucoside in xylem sap of Brassica napus infected with Verticillium longisporum

Salicylic acid (SA) and its glucoside (SAG) were detected in xylem sap of Brassica napus by HPLC–MS. Concentrations of SA and SAG in xylem sap from the root and hypocotyl of the plant, and in extracts of shoots above the hypocotyl, increased after infection with the vascular pathogen Verticillium longisporum. Both concentrations were correlated with disease severity assessed as the reduction in shoot length. Furthermore, SAG levels in shoot extracts were correlated with the amount of V. longisporum DNA in the hypocotyls. Although the concentration of SAG (but not SA) in xylem sap of infected plants gradually declined from 14 to 35 days post infection, SAG levels remained significantly higher than in uninfected plants during the whole experiment. Jasmonic acid (JA) and abscisic acid (ABA) levels in xylem sap were not affected by infection with V. longisporum. SA and SAG extend the list of phytohormones potentially transported from root to shoot with the transpiration stream. The physiological relevance of this transport and its contribution to the distribution of SA in plants remain to be elucidated

Factors affecting costs and utilization of type 2 diabetes healthcare: a cross-sectional survey among 15 hospitals in urban China

<p>Abstract</p> <p>Background</p> <p>Type 2 Diabetes mellitus (T2DM) affects persons of all ages, while also placing heavy economic burdens on national economies and healthcare systems. The study aims to investigate the determinants of direct medical cost (DMC), out-of-pocket (OOP) proportion of the cost, and healthcare utilization associated with T2DM.</p> <p>Methods</p> <p>This cross-sectional study was conducted in four major cities in China. Eligible subjects were adult outpatients who received treatment at one of 15 sampled secondary or tertiary hospitals and consecutively enrolled between March 2007 and May 2007. Generalized estimating equations were used to determine impact factors associated with DMC and healthcare utilization.</p> <p>Results</p> <p>Insurance schemes and receiving insulin therapy were significantly associated with a higher annual DMC of T2DM. For each increase in number of complications, there was about 33% increase in annual DMC. Insurance schemes were significantly associated with the proportions of DMC from pocket. A 7% significantly lower proportion of DMC was paid and 23% more clinic visits (AOR = 1.232, P < 0.001) were made by patients admitted at secondary hospitals than tertiary hospitals. The group with higher income (> 2000 CNY/month) paid 23% less from their pocket, compared with the lower income group. The number of complications also significantly increased the outpatient visits (AOR = 1.064, P < 0.001).</p> <p>Conclusions</p> <p>It implies that preventing complications through the use of more effective treatment regimens is important in order to control the healthcare expenditures of the diseases. Healthcare reform needs to be focused on the medical insurance system and redistribution of patients in hospitals of different levels.</p

Target 2035-update on the quest for a probe for every protein

Twenty years after the publication of the first draft of the human genome, our knowledge of the human proteome is still fragmented. The challenge of translating the wealth of new knowledge from genomics into new medicines is that proteins, and not genes, are the primary executers of biological function. Therefore, much of how biology works in health and disease must be understood through the lens of protein function. Accordingly, a subset of human proteins has been at the heart of research interests of scientists over the centuries, and we have accumulated varying degrees of knowledge about approximately 65% of the human proteome. Nevertheless, a large proportion of proteins in the human proteome (∼35%) remains uncharacterized, and less than 5% of the human proteome has been successfully targeted for drug discovery. This highlights the profound disconnect between our abilities to obtain genetic information and subsequent development of effective medicines. Target 2035 is an international federation of biomedical scientists from the public and private sectors, which aims to address this gap by developing and applying new technologies to create by year 2035 chemogenomic libraries, chemical probes, and/or biological probes for the entire human proteome

Pooling/bootstrap-based GWAS (pbGWAS) identifies new loci modifying the age of onset in PSEN1 p.Glu280Ala Alzheimer\u27s disease

The literature on GWAS (genome-wide association studies) data suggests that very large sample sizes (for example, 50,000 cases and 50,000 controls) may be required to detect significant associations of genomic regions for complex disorders such as Alzheimer\u27s disease (AD). Because of the challenges of obtaining such large cohorts, we describe here a novel sequential strategy that combines pooling of DNA and bootstrapping (pbGWAS) in order to significantly increase the statistical power and exponentially reduce expenses. We applied this method to a very homogeneous sample of patients belonging to a unique and clinically well-characterized multigenerational pedigree with one of the most severe forms of early onset AD, carrying the PSEN1 p.Glu280Ala mutation (often referred to as E280A mutation), which originated as a consequence of a founder effect. In this cohort, we identified novel loci genome-wide significantly associated as modifiers of the age of onset of AD (CD44, rs187116, P=1.29 _ 10?12; NPHP1, rs10173717, P=1.74 _ 10?12; CADPS2, rs3757536, P=1.54 _ 10?10; GREM2, rs12129547, P=1.69 _ 10?13, among others) as well as other loci known to be associated with AD. Regions identified by pbGWAS were confirmed by subsequent individual genotyping. The pbGWAS methodology and the genes it targeted could provide important insights in determining the genetic causes of AD and other complex conditions

CATMoS: Collaborative Acute Toxicity Modeling Suite.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495