Role of a plausible nuisance contributor in the declining obesity-mortality risks over time.

CONTEXT: Recent analyses of epidemiological data including the National Health and Nutrition Examination Survey (NHANES) have suggested that the harmful effects of obesity may have decreased over calendar time. The shifting BMI distribution over time coupled with the application of fixed broad BMI categories in these analyses could be a plausible nuisance contributor to this observed change in the obesity-associated mortality over calendar time. OBJECTIVE: To evaluate the extent to which observed temporal changes in the obesity-mortality association may be due to a shifting population distribution for body mass index (BMI), coupled with analyses based on static, broad BMI categories. DESIGN, SETTING, AND PARTICIPANTS: Simulations were conducted using data from NHANES I and III linked with mortality data. Data from NHANES I were used to fit a true model treating BMI as a continuous variable. Coefficients estimated from this model were used to simulate mortality for participants in NHANES III. Hence, the population-level association between BMI and mortality in NHANES III was fixed to be identical to the association estimated in NHANES I. Hazard ratios (HRs) for obesity categories based on BMI for NHANES III with simulated mortality data were compared to the corresponding estimated HRs from NHANES I. MAIN OUTCOME MEASURES: Change in hazard ratios for simulated data in NHANES III compared to observed estimates from NHANES I. RESULTS: On average, hazard ratios for NHANES III based on simulated mortality data were 29.3% lower than the estimates from NHANES I using observed mortality follow-up. This reduction accounted for roughly three-fourths of the apparent decrease in the obesity-mortality association observed in a previous analysis of these data. CONCLUSIONS: Some of the apparent diminution of the association between obesity and mortality may be an artifact of treating BMI as a categorical variable

Single nucleotide polymorphisms affect both cis- and trans-eQTLs

AbstractSingle nucleotide polymorphisms (SNPs) between microarray probes and RNA targets can affect the performance of expression array by weakening the hybridization. In this paper, we examined the effect of the SNPs on Affymetrix GeneChip probe set summaries and the expression quantitative trait loci (eQTL) mapping results in two eQTL datasets, one from mouse and one from human. We showed that removing SNP-containing probes significantly changed the probe set summaries and the more SNP-containing probes we removed the greater the change. Comparison of the eQTL mapping results between with and without SNP-containing probes showed that less than 70% of the significant eQTL peaks were concordant regardless of the significance threshold. These results indicate that SNPs do affect both probe set summaries and eQTLs (both cis and trans), thus SNP-containing probes should be filtered out to improve the performance of eQTL mapping

Predictors of Weight Change: Findings From an Employee Wellness Program

Introduction: Employers are instituting employee wellness programs that include educational, lifestyle coaching, and weight and other condition management components to address obesity-related issues in the workplace. However, the findings of such wellness initiatives have been mixed. The purpose of this exploratory study is to determine whether the readiness for change measures are important predictors of weight loss in an employee wellness program.Methods: Retrospective data analysis of an employee wellness program conducted in the United States was conducted using data collected between 2014 and 2015 for people with BMI ≥ 30. These participants were assigned to one of two subprograms: weight management or condition management. We assessed the weight change within each program. Further, the relationship between weight change and readiness for change variables for weight, diet, and physical activity were examined by applying multiple linear regression and logistic regression models. The multivariable model included subprogram; gender; age; systolic and diastolic blood pressure; risk factor count; readiness for change for weight, activity, and diet; and stress level as covariates.Results: There were 209 participants in the weight management program and 243 participants in the condition management program who met the criteria for obesity, resulting in a final sample of 452 participants. On average, the weight change for these participants was −0.28 pounds (SD = 15.55) and there was no statistical difference between the weight change in the two programs. When compared to the reference group (maintenance), participants at the action stage of physical activity, on average, lost weight (b = −4.59, p = 0.02). Likewise, participants at the pre-contemplation stage of physical activity lost weight when compared to the maintenance group (b = −26.24, p = 0.000). Participants at the pre-contemplation stage of physical activity had higher odds of achieving at least 5% weight loss than participants at the maintenance stage (OR = 5.80, p = 0.053).Conclusion: Readiness for change for activity may be a predictor of weight change, and may predict the likelihood of achieving clinically significant weight loss. These findings can assist in targeting subjects for participation in such programs. The findings regarding the relationship between readiness for change and weight loss are counterintuitive, and further research is warranted in this area

Open-Label Placebo Treatment for Cancer-Related Fatigue: A Randomized-Controlled Clinical Trial

The purpose of this 21-day assessor blinded, randomized-controlled trial was to compare an open-label placebo (OLP) to treatment as usual (TAU) for cancer survivors with fatigue. This was followed by an exploratory 21-day study in which TAU participants received OLPs while OLP participants in the main study were followed after discontinuing placebos. Cancer survivors (N = 74) who completed cancer treatment 6 months to 10 years prior to enrollment reporting at least moderate fatigue (i.e., ≥4 on a 0–10 scale) were randomized to OLP or TAU. Those randomized to OLP took 2 placebo pills twice a day for 21 days. Compared to those randomized to TAU, OLP participants reported a 29% improvement in fatigue severity (average difference in the mean change scores (MD) 12.47, 95% CI 3.32, 21.61; P = 0.008), medium effect (d = 0.63), and a 39% improvement in fatigue-disrupted quality of life (MD = 11.76, 95% CI 4.65, 18.86; P = 0.002), a large effect (d = 0.76). TAU participants who elected to try OLP for 21-days after the main study reported reductions in fatigue of a similar magnitude for fatigue severity and fatigue-disrupted quality of life (23% and 35%, respectively). OLP may reduce fatigue symptom severity and fatigue-related quality of life disruption in cancer survivors

Two-stage genome-wide association study identifies integrin beta 5 as having potential role in bull fertility

Background: Fertility is one of the most critical factors controlling biological and financial performance of animal production systems and genetic improvement of lines. The objective of this study was to identify molecular defects in the sperm that are responsible for uncompensable fertility in Holstein bulls. We performed a comprehensive genome wide analysis of single nucleotide polymorphisms (SNP) for bull fertility followed by a second-stage replication in additional bulls for a restricted set of markers. Results: In the Phase I association study, we genotyped the genomic sperm DNA of 10 low-fertility and 10 high-fertility bulls using Bovine SNP Gene Chips containing approximately 10,000 random SNP markers. In these animals, 8,207 markers were found to be polymorphic, 97 of which were significantly associated with fertility (p \u3c 0.01). In the Phase II study, we tested the four most significant SNP from the Phase I study in 101 low-fertility and 100 high-fertility bulls, with two SNPs (rs29024867 and rs41257187) significantly replicated. Rs29024867 corresponds to a nucleotide change of C → G 2,190 bp 3′ of the collagen type I alpha 2 gene on chromosome 4, while the rs41257187 (C → T) is in the coding region of integrin beta 5 gene on chromosome 1. The SNP rs41257187 induces a synonymous (Proline → Proline), suggesting disequilibrium with the true causative locus (i), but we found that the incubation of bull spermatozoa with integrin beta 5 antibodies significantly decreased the ability to fertilize oocytes. Our findings suggest that the bovine sperm integrin beta 5 protein plays a role during fertilization and could serve as a positional or functional marker of bull fertility. Conclusion: We have identified molecular markers associated with bull fertility and established that at least one of the genes harboring such variation has a role in fertility. The findings are important in understanding mechanisms of uncompensatory infertility in bulls, and in other male mammals. The findings set the stage for more hypothesis-driven research aimed at discovering the role of variation in the genome that affect fertility and that can be used to identify molecular mechanisms of development. © 2009 Feugang et al; licensee BioMed Central Ltd

Sources of variation in Affymetrix microarray experiments

BACKGROUND: A typical microarray experiment has many sources of variation which can be attributed to biological and technical causes. Identifying sources of variation and assessing their magnitude, among other factors, are important for optimal experimental design. The objectives of this study were: (1) to estimate relative magnitudes of different sources of variation and (2) to evaluate agreement between biological and technical replicates. RESULTS: We performed a microarray experiment using a total of 24 Affymetrix GeneChip(® )arrays. The study included 4(th )mammary gland samples from eight 21-day-old Sprague Dawley CD female rats exposed to genistein (soy isoflavone). RNA samples from each rat were split to assess variation arising at labeling and hybridization steps. A general linear model was used to estimate variance components. Pearson correlations were computed to evaluate agreement between technical and biological replicates. CONCLUSION: The greatest source of variation was biological variation, followed by residual error, and finally variation due to labeling when *.cel files were processed with dChip and RMA image processing algorithms. When MAS 5.0 or GCRMA-EB were used, the greatest source of variation was residual error, followed by biology and labeling. Correlations between technical replicates were consistently higher than between biological replicates

Early outcomes from a randomized, controlled trial of supervised exercise, angioplasty, and combined therapy in intermittent claudication

BACKGROUND: To compare angioplasty (PTA), supervised exercise (SEP) and PTA + SEP in the treatment of intermittent claudication (IC) due to femoropopliteal disease. METHODS: Over a 6-year period, 178 patients (108 men; median age, 70 years) with femoropopliteal lesions suitable for angioplasty were randomized to PTA, SEP, or PTA + SEP. Patients were assessed prior to and at 1 and 3 months post treatment. ISCVS outcome criteria (ankle pressures, treadmill walking distances) and quality of life (QoL) questionnaires (SF-36 and VascuQoL) were analyzed. RESULTS: All groups were well matched at baseline. Twenty-one patients withdrew. Results are as follows: Intragroup analysis: All groups demonstrated significant clinical and QoL improvements (Friedman test, p 0.05). CONCLUSION: SEP should be the primary treatment for the patients with claudication and PTA should be supplemented by an SEP

HDBStat!: A platform-independent software suite for statistical analysis of high dimensional biology data

BACKGROUND: Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. RESULTS: Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. CONCLUSION: HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website