Nutrigenetic Contributions to Dyslipidemia: A Focus on Physiologically Relevant Pathways of Lipid and Lipoprotein Metabolism

Cardiovascular disease (CVD) remains the number one cause of death worldwide, and dyslipidemia is a major predictor of CVD mortality. Elevated lipid concentrations are the result of multiple genetic and environmental factors. Over 150 genetic loci have been associated with blood lipid levels. However, not all variants are present in pathways relevant to the pathophysiology of dyslipidemia. The study of these physiologically relevant variants can provide mechanistic understanding of dyslipidemia and identify potential novel therapeutic targets. Additionally, dietary fatty acids have been evidenced to exert both positive and negative effects on lipid profiles. The metabolism of both dietary and endogenously synthesized lipids can be affected by individual genetic variation to produce elevated lipid concentrations. This review will explore the genetic, dietary, and nutrigenetic contributions to dyslipidemia

Neglecting regression to the mean continues to lead to unwarranted conclusions: Letter regarding The magnitude of weight loss induced by metformin is independently associated with BMI at baseline in newly diagnosed type 2 diabetes: Post-hoc analysis from data of a phase IV open-labeled trial .

As the prevalence of type 2 diabetes mellitus and obesity increases worldwide, scientifically rigorous research is needed in this field to determine effective interventions for the prevention and treatment of these chronic diseases. In a recent study published in this journal, Zhou et al. conclude that metformin, a drug used for treatment of type 2 diabetes mellitus, can be used effectively for weight loss, and that this effect is even more pronounced in individuals who weigh more at baseline. Unfortunately, we believe these results to be due to the regression to the mean (RTM) phenomenon, which weakens the causal inference proposed in this study. The conclusions of Zhou et al. that metformin is an effective strategy for weight loss in individuals with type 2 diabetes mellitus are not substantiated due to the lack of a control group and failure to consider other factors that may have confounded these results

Effect of oral nutritional supplementation on growth in children with undernutrition: A systematic review and meta‐analysis

10.3390/nu13093036Nutrients139303

Informacija apie Organizacijų vadyba: sisteminiai tyrimai / Management of Organizations: Systematic Research 2008, nr. 47

Background: Regression to the mean (RTM) is a statistical phenomenon where initial measurements of a variable in a nonrandom sample at the extreme ends of a distribution tend to be closer to the mean upon a second measurement. Unfortunately, failing to account for the effects of RTM can lead to incorrect conclusions on the observed mean difference between the 2 repeated measurements in a nonrandom sample that is preferentially selected for deviating from the population mean of the measured variable in a particular direction. Study designs that are susceptible to misattributing RTM as intervention effects have been prevalent in nutrition and obesity research. This field often conducts secondary analyses of existing intervention data or evaluates intervention effects in those most at risk (i.e., those with observations at the extreme ends of a distribution). Objectives: To provide best practices to avoid unsubstantiated conclusions as a result of ignoring RTM in nutrition and obesity research. Methods: We outlined best practices for identifying whether RTM is likely to be leading to biased inferences, using a flowchart that is available as a web-based app at https://dustyturner.shinyapps.io/DecisionTreeMeanRegression/. We also provided multiple methods to quantify the degree of RTM. Results: Investigators can adjust analyses to include the RTM effect, thereby plausibly removing its biasing influence on estimating the true intervention effect. Conclusions: The identification of RTM and implementation of proper statistical practices will help advance the field by improving scientific rigor and the accuracy of conclusions. This trial was registered at clinicaltrials.gov as NCT00427193

Clinical validation of cutoff target ranges in newborn screening of metabolic disorders by tandem mass spectrometry: A worldwide collaborative project

PURPOSE:: To achieve clinical validation of cutoff values for newborn screening by tandem mass spectrometry through a worldwide collaborative effort. METHODS:: Cumulative percentiles of amino acids and acylcarnitines in dried blood spots of approximately 25-30 million normal newborns and 10,742 deidentified true positive cases are compared to assign clinical significance, which is achieved when the median of a disorder range is, and usually markedly outside, either the 99th or the 1st percentile of the normal population. The cutoff target ranges of analytes and ratios are then defined as the interval between selected percentiles of the two populations. When overlaps occur, adjustments are made to maximize sensitivity and specificity taking all available factors into consideration. RESULTS:: As of December 1, 2010, 130 sites in 45 countries have uploaded a total of 25,114 percentile data points, 565,232 analyte results of true positive cases with 64 conditions, and 5,341 cutoff values. The average rate of submission of true positive cases between December 1, 2008, and December 1, 2010, was 5.1 cases/day. This cumulative evidence generated 91 high and 23 low cutoff target ranges. The overall proportion of cutoff values within the respective target range was 42% (2,269/5,341). CONCLUSION:: An unprecedented level of cooperation and collaboration has allowed the objective definition of cutoff target ranges for 114 markers to be applied to newborn screening of rare metabolic disorders. © 2011 Lippincott Williams & Wilkins