A tree-based method for the rapid screening of chemical fingerprints

<p>Abstract</p> <p>Background</p> <p>The fingerprint of a molecule is a bitstring based on its structure, constructed such that structurally similar molecules will have similar fingerprints. Molecular fingerprints can be used in an initial phase of drug development for identifying novel drug candidates by screening large databases for molecules with fingerprints similar to a query fingerprint.</p> <p>Results</p> <p>In this paper, we present a method which efficiently finds all fingerprints in a database with Tanimoto coefficient to the query fingerprint above a user defined threshold. The method is based on two novel data structures for rapid screening of large databases: the <it>k</it>D grid and the Multibit tree. The <it>k</it>D grid is based on splitting the fingerprints into <it>k </it>shorter bitstrings and utilising these to compute bounds on the similarity of the complete bitstrings. The Multibit tree uses hierarchical clustering and similarity within each cluster to compute similar bounds. We have implemented our method and tested it on a large real-world data set. Our experiments show that our method yields approximately a three-fold speed-up over previous methods.</p> <p>Conclusions</p> <p>Using the novel <it>k</it>D grid and Multibit tree significantly reduce the time needed for searching databases of fingerprints. This will allow researchers to (1) perform more searches than previously possible and (2) to easily search large databases.</p

CoaSim: A flexible environment for simulating genetic data under coalescent models

BACKGROUND: Coalescent simulations are playing a large role in interpreting large scale intra-specific sequence or polymorphism surveys and for planning and evaluating association studies. Coalescent simulations of data sets under different models can be compared to the actual data to test the importance of different evolutionary factors and thus get insight into these. RESULTS: We have created the CoaSim application as a flexible environment for Monte Carlo simulation of various types of genetic data under equilibrium and non-equilibrium coalescent processes for a variety of applications. Interaction with the tool is through the Guile version of the Scheme scripting language. Scheme scripts for many standard and advanced applications are provided and these can easily be modified by the user for a much wider range of applications. A graphical user interface with less functionality and flexibility is also included. It is primarily intended as an exploratory and educational tool CONCLUSION: CoaSim is a powerful tool because of its flexibility and ease of use. This is illustrated through very varied uses of the application, e.g. evaluation of association mapping methods, parametric bootstrapping, and design and choice of markers for specific question

A fast algorithm for genome-wide haplotype pattern mining

<p>Abstract</p> <p>Background</p> <p>Identifying the genetic components of common diseases has long been an important area of research. Recently, genotyping technology has reached the level where it is cost effective to genotype single nucleotide polymorphism (SNP) markers covering the entire genome, in thousands of individuals, and analyse such data for markers associated with a diseases. The statistical power to detect association, however, is limited when markers are analysed one at a time. This can be alleviated by considering multiple markers simultaneously. The <it>Haplotype Pattern Mining </it>(HPM) method is a machine learning approach to do exactly this.</p> <p>Results</p> <p>We present a new, faster algorithm for the HPM method. The new approach use patterns of haplotype diversity in the genome: locally in the genome, the number of observed haplotypes is much smaller than the total number of possible haplotypes. We show that the new approach speeds up the HPM method with a factor of 2 on a genome-wide dataset with 5009 individuals typed in 491208 markers using default parameters and more if the pattern length is increased.</p> <p>Conclusion</p> <p>The new algorithm speeds up the HPM method and we show that it is feasible to apply HPM to whole genome association mapping with thousands of individuals and hundreds of thousands of markers.</p

Renal function at the time of a myocardial infarction maintains prognostic value for more than 10 years

<p>Abstract</p> <p>Background</p> <p>Renal function is an important predictor of mortality in patients with myocardial infarction (MI), but changes in the impact over time have not been well described.</p> <p>We examined the importance of renal function by estimated GFR (eGFR) and se-creatinine as an independent long-term prognostic factor.</p> <p>Methods</p> <p>Prospective follow-up of 6653 consecutive MI patients screened for entry in the Trandolapril Cardiac Evaluation (TRACE) study. The patients were analysed by Kaplan-Meier survival analysis, landmark analysis and Cox proportional hazard models. Outcome measure was all-cause mortality.</p> <p>Results</p> <p>An eGFR below 60 ml per minute per 1.73 m², consistent with chronic renal disease, was present in 42% of the patients. We divided the patients into 4 groups according to eGFR. Overall, Cox proportional-hazards models showed that eGFR was a significant prognostic factor in the two groups with the lowest eGFR, hazard ratio 1,72 (confidence interval (CI) 1,56-1,91) in the group with the lowest eGFR. Using the eGFR group with normal renal function as reference, we observed an incremental rise in hazard ratio. We divided the follow-up period in 2-year intervals. Landmark analysis showed that eGFR at the time of screening continued to show prognostic effect until 16 years of follow-up. By multivariable Cox regression analysis, the prognostic effect of eGFR persisted for 12 years and of se-creatinine for 10 years. When comparing the lowest group of eGFR with the group with normal eGFR, prognostic significance was present in the entire period of follow-up with a hazard ratio between 1,97 (CI 1,65-2,35) and 1,35 (CI 0,99-1,84) in the 2-year periods.</p> <p>Conclusions</p> <p>One estimate of renal function is a strong and independent long-term prognostic factor for 10-12 years following a MI.</p

Pharmacological Undertreatment of Coronary Risk Factors in Patients with Psoriasis: Observational Study of the Danish Nationwide Registries

BACKGROUND: Patients with psoriasis have increased prevalence of coronary risk factors and limited recent results have suggested that these risk factors are undertreated in patients with psoriasis. This may contribute to the increased risk of cardiovascular diseases observed in patients with psoriasis. OBJECTIVE: To examine the pharmacological treatment of coronary risk factors in patients with severe psoriasis treated with biologic agents in a real-world setting. METHODS AND FINDINGS: Medical history of patients with severe psoriasis treated with biologic agents in the time period 2007-09 was retrieved from a Danish nationwide registry (DERMBIO). Individual-level linkage of nationwide administrative registries of hospitalizations, concomitant medications, and socioeconomic status was performed to gain insights into the use of pharmacological treatment. A total of 693 patients (mean age 46.1 ± 12.7 years, 65.7% male) with severe psoriasis treated with biologic agents were identified. Hypertension, hypercholesterolemia, and diabetes mellitus were identified in 16.6%, 9.2%, and 6.7% of cases, respectively. Patients with severe psoriasis were significantly less likely to receive cardiovascular pharmacotherapy compared to age, sex, and coronary risk factor matched controls. In psoriatic patients with hypertension 27.7% received no antihypertensive pharmacotherapy. Patients with dyslipidemia received cholesterol-lowering medications in 55.8% of cases and patients with diabetes mellitus received angiotensin converting enzyme inhibitors/angiotensin II receptor blockers and cholesterol-lowering medications in 42.1% and 23.7% of cases, respectively. Similar results were found for the subset of patients with >1 coronary risk factor and for high risk patients with established atherosclerotic disease. CONCLUSION: This nationwide study of patients with severe psoriasis demonstrated substantial undertreatment of coronary risk factors. Increased focus on identifying cardiovascular risk factors and initiation of preventive cardiovascular pharmacotherapy in patients with psoriasis is warranted

Establishing Zebrafish as a Novel Exercise Model: Swimming Economy, Swimming-Enhanced Growth and Muscle Growth Marker Gene Expression

Zebrafish has been largely accepted as a vertebrate multidisciplinary model but its usefulness as a model for exercise physiology has been hampered by the scarce knowledge on its swimming economy, optimal swimming speeds and cost of transport. Therefore, we have performed individual and group-wise swimming experiments to quantify swimming economy and to demonstrate the exercise effects on growth in adult zebrafish

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p