Adeniyi J. Adewale

Improving gene set analysis of microarray data by SAM-GS

BackgroundGene-set analysis evaluates the expression of biological pathways, or a priori defined gene sets, rather than that of individual genes, in association with a binary phenotype, and is of great biologic interest in many DNA microarray studies. Gene Set Enrichment Analysis (GSEA) has been applied widely as a tool for gene-set analyses. We describe here some critical problems with GSEA and propose an alternative method by extending the individual-gene analysis method, Significance Analysis of Microarray (SAM), to gene-set analyses (SAM-GS).ResultsUsing a mouse microarray dataset with simulated gene sets, we illustrate that GSEA gives statistical significance to gene sets that have no gene associated with the phenotype (null gene sets), and has very low power to detect gene sets in which half the genes are moderately or strongly associated with the phenotype (truly-associated gene sets). SAM-GS, on the other hand, performs very well. The two methods are also compared in the analyses of three real microarray datasets and relevant pathways, the diverging results of which clearly show advantages of SAM-GS over GSEA, both statistically and biologically. In a microarray study for identifying biological pathways whose gene expressions are associated with p53 mutation in cancer cell lines, we found biologically relevant performance differences between the two methods. Specifically, there are 31 additional pathways identified as significant by SAM-GS over GSEA, that are associated with the presence vs. absence of p53. Of the 31 gene sets, 11 actually involve p53 directly as a member. A further 6 gene sets directly involve the extrinsic and intrinsic apoptosis pathways, 3 involve the cell-cycle machinery, and 3 involve cytokines and/or JAK/STAT signaling. Each of these 12 gene sets, then, is in a direct, well-established relationship with aspects of p53 signaling. Of the remaining 8 gene sets, 6 have plausible, if less well established, links with p53.ConclusionWe conclude that GSEA has important limitations as a gene-set analysis approach for microarray experiments for identifying biological pathways associated with a binary phenotype. As an alternative statistically-sound method, we propose SAM-GS. A free Excel Add-In for performing SAM-GS is available for public use.

Health researchers in Alberta: an exploratory comparison of defining characteristics and knowledge translation activities

BackgroundCanadian funding agencies are no longer content to support research that solely advances scientific knowledge, and key directives are now in place to promote research transfer to policy- and decision-makers. Therefore, it is necessary to improve our understanding of how researchers are trained and supported to facilitate knowledge translation activities. In this study, we investigated differences in health researcher characteristics and knowledge translation activities.MethodsOur sample consisted of 240 health researchers from three Alberta universities. Respondents were classified by research domain [basic (n = 72) or applied (n = 168)] and faculty [medical school (n = 128) or other health science (n = 112)]. We examined our findings using Mode I and Mode II archetypes of knowledge production, which allowed us to consider the scholarly and social contexts of knowledge production and translation.ResultsDifferences among health researcher professional characteristics were not statistically significant. There was a significant gender difference in the applied researcher faculty group, which was predominantly female (p < .05). Research domain was linked to translation activities. Applied researchers reported engaging in significantly more Mode II activities than basic researchers (p < .001), and scored higher than basic researchers regarding the perceived importance of translation activities (Mode I, p = .01; Mode II, p < .001). Main effects of faculty were limited to engaged dissemination (medical school < other faculties; p = .025) and number of publications (medical school > other faculties; p = .004). There was an interaction effect for research domain and faculty group for number of publications (p = .01), in that applied researchers in medical faculties published more than their peers in other faculty groups.ConclusionOur findings illustrate important differences between health researchers and provide beginning insights into their professional characteristics and engagement in Mode I and Mode II activities. A future study designed to examine these dimensions in greater detail, including potential covariates across more varied institutions, would yield richer insights and enable an examination of relative influences, needs and costs of each mode of activity.

Lipid-Altering Efficacy and Safety of Ezetimibe/Simvastatin Versus Atorvastatin in Patients With Hypercholesterolemia and the Metabolic Syndrome (from the VYMET Study)

Patients with the metabolic syndrome are at an increased risk of cardiovascular disease and might require intensive lipid therapy. Many patients remain at the starting dose of lipid therapy and might not be titrated up to a higher dose. The present double-blind, randomized, 6-week study assessed the lipid-lowering efficacy of ezetimibe/simvastatin 10/20 mg versus atorvastatin 10 or 20 mg, and ezetimibe/simvastatin 10/40 mg versus atorvastatin 40 mg in 1,128 patients with hypercholesterolemia and the metabolic syndrome. The primary end point was the percentage of change from baseline in low-density lipoprotein (LDL) cholesterol. Additional end points included changes in other lipids, lipoprotein ratios, high-sensitivity C-reactive protein, and attainment of prespecified lipid levels. Significantly greater improvements in the levels of LDL cholesterol, non-high-density lipoprotein cholesterol, apolipoprotein B, and lipid/lipoprotein ratios resulted with ezetimibe/simvastatin compared with atorvastatin at all specified dose comparisons (p <0.001). The attainment of prespecified LDL cholesterol and non-high-density lipoprotein cholesterol levels was also significantly greater with ezetimibe/simvastatin than with atorvastatin at all dose comparisons (p <0.05). High-density lipoprotein cholesterol increases were significantly greater with ezetimibe/simvastatin 10/20 mg than with atorvastatin 10 mg (p <0.05) and ezetimibe/simvastatin 10/40 mg than with atorvastatin 40 mg (p <0.01). The changes in triglycerides, very low-density lipoprotein cholesterol, and high-sensitivity C-reactive protein were similar for both treatments. The incidence of liver, muscle, and gastrointestinal-, hepatitis- and allergic reaction/rash-related adverse events were low and generally similar to those in previous studies of ezetimibe/simvastatin and/or atorvastatin. In conclusion, ezetimibe/simvastatin was more likely to result in lipid treatment end points than atorvastatin and was generally well tolerated at the doses compared in our patients.

Long-Term Safety and Efficacy of Triple Combination Ezetimibe/Simvastatin Plus Extended-Release Niacin in Patients With Hyperlipidemia

The safety and efficacy of combination ezetimibe/simvastatin (E/S) plus extended-release niacin was assessed in 942 patients with type IIa/IIb hyperlipidemia for 64 weeks in a randomized, double-blind study. Patients received E/S (10/20 mg) plus niacin (to 2 g) or E/S (10/20 mg) for 64 weeks, or niacin (to 2 g) for 24 weeks and then E/S (10/20 mg) plus niacin (2 g) or E/S (10/20 mg) for an additional 40 weeks. The primary end point, the safety of E/S plus niacin, included prespecified adverse events (ie, liver, muscle, discontinuations due to flushing, gallbladder-related, cholecystectomy, fasting glucose changes, new-onset diabetes). The secondary end points included the percentage of change from baseline in high-density lipoprotein (HDL) cholesterol, triglycerides, non-HDL cholesterol, and low-density lipoprotein cholesterol, other lipids, lipoprotein ratios and high-sensitivity C-reactive protein. The anticipated niacin-associated flushing led to a greater rate of study discontinuations with the E/S plus niacin regimen than with E/S alone (0.7%, p <0.001). The rate of liver and muscle adverse events was low (<1%) in both groups. Four patients had gallbladder-related adverse events; 1 patient in the E/S and 1 in the E/S plus niacin group underwent cholecystectomy. The occurrence of new-onset diabetes was 3.1% for the E/S and 4.9% for the E/S plus niacin group. The fasting glucose levels increased to greater than baseline during the first 12 weeks (E/S, 3.2 mg/dl; E/S plus niacin, 7.7 mg/dl) and gradually decreased to pretreatment levels by 64 weeks in both groups. E/S plus niacin significantly improved HDL cholesterol, triglycerides, non-HDL cholesterol, low-density lipoprotein cholesterol, apolipoprotein B and A-I, and lipoprotein ratios compared with E/S (p <or=0.004). The changes in high-sensitivity C-reactive protein were comparable for both groups. In conclusion, the combination of E/S plus niacin was generally well tolerated, aside from niacin-associated flushing, and was significantly superior to E/S alone in improving several lipoprotein parameters during a 64-week trial in patients with hyperlipidemia. E/S plus niacin provided a broad, lipid-altering therapeutic option for these patients, even in the presence of diabetes with glucose monitoring.

Understanding hierarchical linear models: applications in nursing research.

Nurses practice within hierarchical organizations and occupational structures. Hence, data emanating from nursing environments are structured, often inherently, hierarchically. From the perspective of ordinary regression, such structuring constitutes a statistical problem because this violates the assumption that we have observed independent and identical cases. A preferable approach is to employ analytical methods that mesh with the kinds of natural aggregations present in nursing environments. Consequently, there has been increasing interest in applying hierarchical, or multilevel, linear models to nursing contexts because this powerful analytical tool recognizes and accommodates naturally hierarchical data structures. The purpose of this article is to foster an understanding of both the strengths and limitations of hierarchical models. A hypothetical nursing example is progressively extended from the most basic hierarchical linear model toward a full two-level model. The structural similarities between two-level and three-level models are pointed out while focusing on the hierarchical nature of models rather than statistical technicalities. The limitations of hierarchical models are discussed also.

Safety and Efficacy of Ezetimibe/Simvastatin Combination Versus Atorvastatin Alone in Adults ≥65 Years of Age With Hypercholesterolemia and With or at Moderately High/High Risk for Coronary Heart Disease (the VYTELD Study)

Higher than 80% of coronary heart disease-related mortality occurs in patients ≥65 years of age. Guidelines recommend low-density lipoprotein (LDL) cholesterol targets for these at-risk patients; however, few clinical studies have evaluated lipid-lowering strategies specifically in older adults. This multicenter, 12-week, randomized, double-blind, parallel-group trial evaluated the efficacy and safety of the usual starting dose of ezetimibe/simvastatin (10/20 mg) versus atorvastatin 10 or 20 mg and the next higher dose of ezetimibe/simvastatin (10/40 mg) versus atorvastatin 40 mg in 1,289 hypercholesterolemic patients ≥65 years of age with or without cardiovascular disease. Patients randomized to ezetimibe/simvastatin had greater percent decreases in LDL cholesterol (-54.2% for 10/20 mg vs -39.5% and -46.6% for atorvastatin 10 and 20 mg, respectively; -59.1% for 10/40 mg vs -50.8% for atorvastatin 40 mg; p <0.001 for all comparisons) and the number attaining LDL cholesterol <70 mg/dl (51.3% for 10/20 mg, 68.2% for 10/40 mg) and <100 mg/dl (83.6% for 10/20 mg; 90.3% for 10/40 mg) was significantly larger compared to those receiving atorvastatin for all prespecified dose comparisons (p <0.05 to <0.001). A significantly larger percentage of high-risk patients achieved LDL cholesterol <70 mg/dl on ezetimibe/simvastatin 10/20 mg (54.3%) versus atorvastatin 10 mg (10.9%, p <0.001) or 20 mg (28.9%, p <0.001) and ezetimibe/simvastatin 10/40 mg (69.2%) versus atorvastatin 40 mg (38.2%, p <0.001), and a significantly larger percentage of intermediate-risk patients achieved LDL cholesterol <100 mg/dl on ezetimibe/simvastatin 10/20 mg (82.1%) versus atorvastatin 10 mg (59.3%, p <0.05). Improvements in non-high-density lipoprotein cholesterol, total cholesterol, apolipoprotein B, and lipoprotein ratios were significantly greater with ezetimibe/simvastatin than atorvastatin for all comparisons (p <0.01 to <0.001). High-density lipoprotein cholesterol and triglyceride results were variable. All treatments were generally well tolerated. In conclusion, ezetimibe/simvastatin provided significantly greater improvements in key lipid parameters and higher attainment of LDL cholesterol targets than atorvastatin, with comparable tolerability.

Effect of Extended-Release Niacin on New-Onset Diabetes Among Hyperlipidemic Patients Treated With Ezetimibe/Simvastatin in a Randomized Controlled Trial

OBJECTIVE To determine the effect of niacin on fasting glucose (FG) and new-onset diabetes in statin/ezetimibe-treated patients. RESEARCH DESIGN AND METHODS This was a prespecified secondary analysis among 942 hyperlipidemic patients randomized to ezetimibe/simvastatin (E/S; 10/20 mg) or E/S + extended-release niacin (N; titrated to 2 g) over 64 weeks. RESULTS FG levels peaked by 8–12 weeks, then declined even without antidiabetic medication. At 64 weeks, 3.5% taking E/S+N versus 2.6% taking E/S met criteria for new-onset diabetes (P = 0.66). An additional 1.4% taking E/S+N versus 0.4% taking E/S transiently met criteria for diabetes and then remitted (P = 0.46). Of 28 new-diabetes diagnoses in the E/S+N group, 25 occurred by 24 weeks. Among patients with baseline diabetes, 13.9% taking E/S+N and 11.6% taking E/S underwent antidiabetic treatment modification. CONCLUSIONS Increased FG and new-onset diabetes with E/S+N occurred mainly around the time of initial uptitration of N and often improved or remitted without specific treatment.

A Biological Evaluation of Six Gene Set Analysis Methods for Identification of Differentially Expressed Pathways in Microarray Data

Gene-set analysis of microarray data evaluates biological pathways, or gene sets, for their differential expression by a phenotype of interest. In contrast to the analysis of individual genes, gene-set analysis utilizes existing biological knowledge of genes and their pathways in assessing differential expression. This paper evaluates the biological performance of five gene-set analysis methods testing “self-contained null hypotheses” via subject sampling, along with the most popular gene-set analysis method, Gene Set Enrichment Analysis (GSEA). We use three real microarray analyses in which differentially expressed gene sets are predictable biologically from the phenotype. Two types of gene sets are considered for this empirical evaluation: one type contains “truly positive” sets that should be identified as differentially expressed; and the other type contains “truly negative” sets that should not be identified as differentially expressed. Our evaluation suggests advantages of SAM-GS, Global, and ANCOVA Global methods over GSEA and the other two methods.

Robust designs for generalized linear models with possible overdispersion and misspecified link functions

We discuss robust designs for generalized linear models with protection for possible departures from the usual model assumptions. Besides possible inaccuracy in an assumed linear predictor, both problems of overdispersion and misspecification in link function are addressed. For logistic and Poisson models, as examples, we incorporate the variance function prescribed by a superior model similar to a generalized linear mixed model to address overdispersion, and adopt a parameterized generalized family of link functions to deal with the problem of link misspecification. The design criterion is the average mean squared prediction error (AMSPE). The exact optimal design, which minimizes the AMSPE, is also presented using examples on the toxicity of ethylene oxide to grain beetles, and on Ames Salmonella Assay.

A Randomized Clinical Trial of Elk Velvet Antler in Rheumatoid Arthritis

This article examines the effects of elk velvet antler on joint pain and swelling, patient/physician global assessment of disease activity, functional ability, quality of life, blood levels of C-reactive protein, and adverse events in persons with stage 2 to 3 rheumatoid arthritis experiencing residual symptoms after standard treatment. Patients (N=168) were enrolled in a 6-month randomized, triple-blind, placebo-controlled clinical trial. Instruments included the Arthritis Impact Measurement Scale, the Health Assessment Questionnaire, tender and swollen joint counts, and 100 mm-length visual analogue scales, along with blood tests. There were no significant differences between groups on any measures. The pattern of change of the measures across time points was essentially the same for both groups. Although some patients reported clinical improvements in their symptoms, there were no statistically significant differences between groups. Overall, elk velvet antler does not effectively manage residual symptoms in patients with rheumatoid arthritis.