scholarly journals The Opposing Effect of Hedonic and Eudaimonic Happiness on Gene Expression is Correlated Noise

2016 ◽  
Author(s):  
Jeffrey A. Walker
Keyword(s):  
Gene Expression ◽  
Fixed Effects ◽  
Regression Coefficients ◽  
Standard Errors ◽  
Type I ◽  
Correlated Noise ◽  
Partial Regression ◽  
Inflated Type ◽  
Opposing Effects ◽  
Eudaimonic Happiness

AbstractBackgroundThis paper presents a re-analysis of the gene set data from Fredrickson et al. 2013 and Fredrickson et al. 2015 which purportedly showed opposing effects of hedonic and eudaimonic happiness on the expression levels of a set of genes that have been correlated with social adversity. Fredrickson et al. 2015 used a linear model of fixed effects with correlated error (using GLS) to estimate the partial regression coefficients.MethodsThe standardized effects of hedonic and eudaimonic happiness on CTRA gene set expression estimated by GLS was compared to estimates using multivariate (OLS) linear models and generalized estimating equation (GEE) models. The OLS estimates were tested using a bootstrap t-test, O’Brien’s OLS test, a permutation t test, and the rotation z-test. The GEE estimates were tested using a Wald test with robust standard errors. The performance (type I, type II, and type M error) of all tests was investigated using a Monte Carlo simulation of data modeled after the 2015 dataset.ResultsStandardized OLS effects (mean partial regression coefficients) of Hedonia and Eudaimonia on gene expression levels are very small in both the 2013 and 2015 data, as well as the combined data.The p-values from all tests fail to reject any of the null models. The GEE estimates and tests are nearly identical to the OLS estimates and tests. By contrast, the GLS estimates are inconsistent between data sets, but in each dataset, at least one coefficient is large and highly statistically significant. The Monte Carlo simulation of error rates shows inflated type I error from the GLS test on data with a similar correlation structure to that in the 2015 dataset, and this error rate increases as the number of outcomes increases relative to the number of subjects. Bootstrap and permutation GLS distributions suggest that the GLS model not only results in downward biased standard errors but also inflated coefficients. Both distributions also show the expected, strong, negative correlation between the coefficients for Hedonia and Eudaimonia.DiscussionThe results fail to support opposing effects, or any detectable effect, of hedonic and eudaimonic well being on the pattern of gene expression. The apparently replicated pattern of hedonic and eudaimonic effects on gene expression is most parsimoniously explained as "correlated noise" due to the geometry of multiple regression. A linear mixed model for estimating fixed effects in designs with many repeated measures or outcomes should be used cautiously because of the potentially inflated type 1 and type M error.

scholarly journals Monte Carlo simulation of OLS and linear mixed model inference of phenotypic effects on gene expression

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2575
Author(s):  
Jeffrey A. Walker
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Fixed Effects ◽  
Linear Mixed Model ◽  
Type I Error ◽  
Well Being ◽  
Standard Errors ◽  
Type I ◽  
Gene Set ◽  
Inflated Type

BackgroundSelf-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defineda priori. Many self-contained gene set analysis methods have been developed but the performance of these methods for phenotypes that are continuous rather than discrete and with multiple nuisance covariates has not been well studied. Here, I use Monte Carlo simulation to evaluate the performance of both novel and previously published (and readily available via R) methods for inferring effects of a continuous predictor on mean expression in the presence of nuisance covariates. The motivating data are a high-profile dataset which was used to show opposing effects of hedonic and eudaimonic well-being (or happiness) on the mean expression level of a set of genes that has been correlated with social adversity (the CTRA gene set). The original analysis of these data used a linear model (GLS) of fixed effects with correlated error to infer effects ofHedoniaandEudaimoniaon mean CTRA expression.MethodsThe standardized effects ofHedoniaandEudaimoniaon CTRA gene set expression estimated by GLS were compared to estimates using multivariate (OLS) linear models and generalized estimating equation (GEE) models. The OLS estimates were tested using O’Brien’s OLS test, Anderson’s permutation ${r}_{F}^{2}$-test, two permutationF-tests (including GlobalAncova), and a rotationz-test (Roast). The GEE estimates were tested using a Wald test with robust standard errors. The performance (Type I, II, S, and M errors) of all tests was investigated using a Monte Carlo simulation of data explicitly modeled on the re-analyzed dataset.ResultsGLS estimates are inconsistent between data sets, and, in each dataset, at least one coefficient is large and highly statistically significant. By contrast, effects estimated by OLS or GEE are very small, especially relative to the standard errors. Bootstrap and permutation GLS distributions suggest that the GLS results in downward biased standard errors and inflated coefficients. The Monte Carlo simulation of error rates shows highly inflated Type I error from the GLS test and slightly inflated Type I error from the GEE test. By contrast, Type I error for all OLS tests are at the nominal level. The permutationF-tests have ∼1.9X the power of the other OLS tests. This increased power comes at a cost of high sign error (∼10%) if tested on small effects.DiscussionThe apparently replicated pattern of well-being effects on gene expression is most parsimoniously explained as “correlated noise” due to the geometry of multiple regression. The GLS for fixed effects with correlated error, or any linear mixed model for estimating fixed effects in designs with many repeated measures or outcomes, should be used cautiously because of the inflated Type I and M error. By contrast, all OLS tests perform well, and the permutationF-tests have superior performance, including moderate power for very small effects.

scholarly journals Functional traits and community composition: multilevel models outperform community-weighted means

2017 ◽  
Author(s):  
Jesse E D Miller ◽  
Anthony Ives ◽  
Ellen Damschen
Keyword(s):  
Functional Traits ◽  
Simulation Study ◽  
Community Assembly ◽  
Fixed Effects ◽  
Multilevel Models ◽  
Type I Error ◽  
Type I ◽  
Type I Errors ◽  
Weighted Means ◽  
Inflated Type

1. Plant functional traits are increasingly being used to infer mechanisms about community assembly and predict global change impacts. Of the several approaches that are used to analyze trait-environment relationships, one of the most popular is community-weighted means (CWM), in which species trait values are averaged at the site level. Other approaches that do not require averaging are being developed, including multilevel models (MLM, also called generalized linear mixed models). However, relative strengths and weaknesses of these methods have not been extensively compared. 2. We investigated three statistical models for trait-environment associations: CWM, a MLM in which traits were not included as fixed effects (MLM1), and a MLM with traits as fixed effects (MLM2). We analyzed a real plant community dataset to investigate associations between two traits and one environmental variable. We then analyzed permutations of the dataset to investigate sources of type I errors, and performed a simulation study to compare the statistical power of the methods. 3. In the analysis of real data, CWM gave highly significant associations for both traits, while MLM1 and MLM2 did not. Using P-values derived by simulating the data using the fitted MLM2, none of the models gave significant associations, showing that CWM had inflated type I errors (false positives). In the permutation tests, MLM2 performed the best of the three approaches. MLM2 still had inflated type I error rates in some situations, but this could be corrected using bootstrapping. The simulation study showed that MLM2 always had as good or better power than CWM. These simulations also confirmed the causes of type I errors from the permutation study. 4. The MLM that includes main effects of traits (MLM2) is the best method for identifying trait-environmental association in community assembly, with better type I error control and greater power. Analyses that regress CWMs on continuous environmental variables are not reliable because they are likely to produce type I errors.

The Effects of Rainfall and Temperature on Percolation Through Drain Gauges

1934 ◽  
Vol 24 (1) ◽  
pp. 105-135 ◽  
Author(s):  
R. S. Koshal ◽  
R. A. Fisher
Keyword(s):  
Numerical Methods ◽  
Soil Mass ◽  
Rate Of Change ◽  
Regression Coefficients ◽  
Standard Errors ◽  
Regression Equations ◽  
Partial Regression ◽  
Direct Knowledge ◽  
The Mean ◽  
Partial Depletion

Summary1. Partial regression equations representing the average drainage observed in any month in terms of the temperature and rainfall of that month, and including terms representing the mean secular rate of change of the drainage discharge and of its regression coefficients on rainfall and temperature, have been fitted to the thirty-six series of observations provided by the three Rothamsted drain gauges in the twelve months of the year.2. An account is given of adequate and direct numerical methods of handling equations involving observed quantities, and chosen functions of them, as independent variates, and of calculating standard errors appropriate to the several sorts of comparison which are to be made.3. In the absence of direct knowledge of the amount of water contained from time to time in the soil mass of the gauge it has been customary to assume that the lower average drainage of the summer months is directly due to a greater amount of evaporation taking place in these months. The results of the present enquiry direct attention to a second possibility, namely that the water content of the gauges differs considerably at different times of the year, and that the high drainage in winter is in part to be ascribed to the accumulation of water during the rainy months of autumn, while the lower drainage in summer is due to the partial depletion of the gauges during the lower rainfall of the spring months.

Neuroserpin in Bipolar Disorder

2020 ◽  
Vol 20 (7) ◽  
pp. 518-523
Author(s):  
Rugül Köse Çinar
Keyword(s):  
Gene Expression ◽  
Bipolar Disorder ◽  
Polymerase Chain Reaction Method ◽  
Type I ◽  
Healthy Controls ◽  
Neuroprotective Effects ◽  
Expression Levels ◽  
Disease States ◽  
Cord Injury ◽  
System Functioning

Objective: Neuroserpin is a serine protease inhibitor predominantly expressed in the nervous system functioning mainly in neuronal migration and axonal growth. Neuroprotective effects of neuroserpin were shown in animal models of stroke, brain, and spinal cord injury. Postmortem studies confirmed the involvement of neuroserpin in Alzheimer’s disease. Since altered adult neurogenesis was postulated as an aetiological mechanism for bipolar disorder, the possible effect of neuroserpin gene expression in the disorder was evaluated. Methods: Neuroserpin mRNA expression levels were examined in the peripheral blood of bipolar disorder type I manic and euthymic patients and healthy controls using the polymerase chain reaction method. The sample comprised of 60 physically healthy, middle-aged men as participants who had no substance use disorder. Results: The gene expression levels of neuroserpin were found lower in the bipolar disorder patients than the healthy controls (p=0.000). The neuroserpin levels did not differ between mania and euthymia (both 96% down-regulated compared to the controls). Conclusion: Since we detected differences between the patients and the controls, not the disease states, the dysregulation in the neuroserpin gene could be interpreted as a result of the disease itself.

scholarly journals Modulation of Chicken Intestinal Immune Gene Expression by Small Cationic Peptides as Feed Additives during the First Week Posthatch

2013 ◽  
Vol 20 (9) ◽  
pp. 1440-1448 ◽  
Author(s):  
Michael H. Kogut ◽  
Kenneth J. Genovese ◽  
Haiqi He ◽  
Christina L. Swaggerty ◽  
Yiwei Jiang
Keyword(s):  
Gene Expression ◽  
Proinflammatory Cytokines ◽  
Proinflammatory Cytokine ◽  
Feed Additives ◽  
Feed Additive ◽  
Cationic Peptides ◽  
Type I ◽  
Immune Gene ◽  
Content Type ◽  
Functional Efficiency

ABSTRACTWe have been investigating modulation strategies tailored around the selective stimulation of the host's immune system as an alternative to direct targeting of microbial pathogens by antibiotics. One such approach is the use of a group of small cationic peptides (BT) produced by a Gram-positive soil bacterium,Brevibacillus texasporus. These peptides have immune modulatory properties that enhance both leukocyte functional efficiency and leukocyte proinflammatory cytokine and chemokine mRNA transcription activitiesin vitro. In addition, when provided as a feed additive for just 4 days posthatch, BT peptides significantly induce a concentration-dependent protection against cecal and extraintestinal colonization bySalmonella entericaserovar Enteritidis. In the present studies, we assessed the effects of feeding BT peptides on transcriptional changes on proinflammatory cytokines, inflammatory chemokines, and Toll-like receptors (TLR) in the ceca of broiler chickens with and withoutS. Enteritidis infection. After feeding a BT peptide-supplemented diet for the first 4 days posthatch, chickens were then challenged withS. Enteritidis, and intestinal gene expression was measured at 1 or 7 days postinfection (p.i.) (5 or 11 days of age). Intestinal expression of innate immune mRNA transcripts was analyzed by quantitative real-time PCR (qRT-PCR). Analysis of relative mRNA expression showed that a BT peptide-supplemented diet did not directly induce the transcription of proinflammatory cytokine, inflammatory chemokine, type I/II interferon (IFN), or TLR mRNA in chicken cecum. However, feeding the BT peptide-supplemented diet primed cecal tissue for increased (P≤ 0.05) transcription of TLR4, TLR15, and TLR21 upon infection withS. Enteritidis on days 1 and 7 p.i. Likewise, feeding the BT peptides primed the cecal tissue for increased transcription of proinflammatory cytokines (interleukin 1β [IL-1β], IL-6, IL-18, type I and II IFNs) and inflammatory chemokine (CxCLi2) in response toS. Enteritidis infection 1 and 7 days p.i. compared to the chickens fed the basal diet. These small cationic peptides may prove useful as alternatives to antibiotics as local immune modulators in neonatal poultry by providing prophylactic protection againstSalmonellainfections.

scholarly journals Understanding, Choosing, and Unifying Multilevel and Fixed Effect Approaches

2020 ◽  
pp. 1-20
Author(s):  
Chad Hazlett ◽  
Leonard Wainstein
Keyword(s):  
Random Effects ◽  
Fixed Effects ◽  
Multilevel Models ◽  
Standard Errors ◽  
Point Estimate ◽  
Fe Model ◽  
Grouped Data ◽  
Coefficient Estimates ◽  
Political Science Education ◽  
Robust Standard Errors

Abstract When working with grouped data, investigators may choose between “fixed effects” models (FE) with specialized (e.g., cluster-robust) standard errors, or “multilevel models” (MLMs) employing “random effects.” We review the claims given in published works regarding this choice, then clarify how these approaches work and compare by showing that: (i) random effects employed in MLMs are simply “regularized” fixed effects; (ii) unmodified MLMs are consequently susceptible to bias—but there is a longstanding remedy; and (iii) the “default” MLM standard errors rely on narrow assumptions that can lead to undercoverage in many settings. Our review of over 100 papers using MLM in political science, education, and sociology show that these “known” concerns have been widely ignored in practice. We describe how to debias MLM’s coefficient estimates, and provide an option to more flexibly estimate their standard errors. Most illuminating, once MLMs are adjusted in these two ways the point estimate and standard error for the target coefficient are exactly equal to those of the analogous FE model with cluster-robust standard errors. For investigators working with observational data and who are interested only in inference on the target coefficient, either approach is equally appropriate and preferable to uncorrected MLM.

scholarly journals STING and cGAS gene expressions were downregulated among HIV-1-infected persons after antiretroviral therapy

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Lorena Leticia Peixoto de Lima ◽  
Allysson Quintino Tenório de Oliveira ◽  
Tuane Carolina Ferreira Moura ◽  
Ednelza da Silva Graça Amoras ◽  
Sandra Souza Lima ◽  
...  
Keyword(s):  
Gene Expression ◽  
Viral Load ◽  
T Cell ◽  
Antiretroviral Therapy ◽  
Cell Count ◽  
Enzyme Linked Immunosorbent Assay ◽  
Type I ◽  
Α Level ◽  
The Impact ◽  
Hiv 1

Abstract Background The HIV-1 epidemic is still considered a global public health problem, but great advances have been made in fighting it by antiretroviral therapy (ART). ART has a considerable impact on viral replication and host immunity. The production of type I interferon (IFN) is key to the innate immune response to viral infections. The STING and cGAS proteins have proven roles in the antiviral cascade. The present study aimed to evaluate the impact of ART on innate immunity, which was represented by STING and cGAS gene expression and plasma IFN-α level. Methods This cohort study evaluated a group of 33 individuals who were initially naïve to therapy and who were treated at a reference center and reassessed 12 months after starting ART. Gene expression levels and viral load were evaluated by real-time PCR, CD4+ and CD8+ T lymphocyte counts by flow cytometry, and IFN-α level by enzyme-linked immunosorbent assay. Results From before to after ART, the CD4+ T cell count and the CD4+/CD8+ ratio significantly increased (p < 0.0001), the CD8+ T cell count slightly decreased, and viral load decreased to undetectable levels in most of the group (84.85%). The expression of STING and cGAS significantly decreased (p = 0.0034 and p = 0.0001, respectively) after the use of ART, but IFN-α did not (p = 0.1558). Among the markers evaluated, the only markers that showed a correlation with each other were STING and CD4+ T at the time of the first collection. Conclusions ART provided immune recovery and viral suppression to the studied group and indirectly downregulated the STING and cGAS genes. In contrast, ART did not influence IFN-α. The expression of STING and cGAS was not correlated with the plasma level of IFN-α, which suggests that there is another pathway regulating this cytokine in addition to the STING–cGAS pathway.

scholarly journals Testing for treatment effect in covariate-adaptive randomized trials with generalized linear models and omitted covariates

2021 ◽  
pp. 096228022110082
Author(s):  
Yang Li ◽  
Wei Ma ◽  
Yichen Qin ◽  
Feifang Hu
Keyword(s):  
Generalized Linear Models ◽  
Treatment Effect ◽  
Linear Models ◽  
Type I Error ◽  
Type I ◽  
Test Statistic ◽  
Asymptotic Results ◽  
Adaptive Randomization ◽  
Adjustment Method ◽  
Inflated Type

Concerns have been expressed over the validity of statistical inference under covariate-adaptive randomization despite the extensive use in clinical trials. In the literature, the inferential properties under covariate-adaptive randomization have been mainly studied for continuous responses; in particular, it is well known that the usual two-sample t-test for treatment effect is typically conservative. This phenomenon of invalid tests has also been found for generalized linear models without adjusting for the covariates and are sometimes more worrisome due to inflated Type I error. The purpose of this study is to examine the unadjusted test for treatment effect under generalized linear models and covariate-adaptive randomization. For a large class of covariate-adaptive randomization methods, we obtain the asymptotic distribution of the test statistic under the null hypothesis and derive the conditions under which the test is conservative, valid, or anti-conservative. Several commonly used generalized linear models, such as logistic regression and Poisson regression, are discussed in detail. An adjustment method is also proposed to achieve a valid size based on the asymptotic results. Numerical studies confirm the theoretical findings and demonstrate the effectiveness of the proposed adjustment method.

scholarly journals SAT0299 PROLIFERATION, MIGRATION AND CONTRACTION ARE DIFFERENT BETWEEN TGFΒ AND PDGF STIMULATED DERMAL FIBROBLASTS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1094.2-1095
Author(s):  
A. S. Siebuhr ◽  
S. F. Madsen ◽  
M. Karsdal ◽  
A. C. Bay-Jensen ◽  
P. Juhl
Keyword(s):  
Gene Expression ◽  
Treatment Initiation ◽  
Human Fibroblasts ◽  
Calf Serum ◽  
Collagen Type I ◽  
Dermal Fibroblasts ◽  
Type I ◽  
Full Time ◽  
Ecm Remodeling ◽  
Full Time Employee

Background:Systemic sclerosis has vascular, inflammatory and fibrotic components, which may be associated with different growth factors and cytokines. Platelet derived growth factor (PDGF) is associated with the vasculature, whereas tumor necrosis factor beta (TGFβ) is associated with inflammation and fibrosis. We have developed a fibroblast model system of dermal fibrosis for anti-fibrotic drugs testing, but the effect of the fibroblasts mechanistic properties are unknown.Objectives:We investigated different mechanical capacities of PDGF and TGFβ treated human healthy dermal fibroblasts in the SiaJ setting.Methods:Primary human healthy dermal fibroblasts were grown in DMEM medium containing 0.4% fetal calf serum, ficoll (to produce a crowded environment) and ascorbic acid for up to 17 days. A wound was induced by scratching the cells at 0, 1, 3 or 7 days after treatment initiation. Wound closure was followed for 3 days. Contraction capacity was tested by creating gels of human fibroblasts produced collagens containing dermal fibroblasts and contraction was assessed at day 2 by calculating the percentage of gel size to total well size. Collagen type I, III and VI formation (PRO-C1, PRO-C3 and PRO-C6) and fibronectin (FBN-C) were evaluated by validated ELISAs (Nordic Bioscience). Gene expression was analyzed after 2 days in culture. Statistical analyses included One-way ANOVA and student’s t-test.Results:Generally, PDGF closed the wound in half the time of w/o and TGFβ, when treatment and cells are added concurrently or scratched one day after treatment initiation. When treatments were added 3 or 7 days prior to scratch, the cells treated with PDGF had proliferated to a higher degree than w/o and TGFβ. A consequence of this, was that when cells were scratch the sheet of cells produced was lifted from the bottom and fold over itself, leaving a much greater scratch than in the other treatments. However, despite this increased gap the PDGF treated cells closed the wound at the same time as w/o and TGFβ, confirming the results of the cells scratched at day 0 and 1.Inhibition of contraction by ML-7 of otherwise untreated cells inhibited contraction significantly compared to untreated cells alone (p=0.0009). Contraction was increased in both TGFβ and PDGF treated cells compared to untreated cells (both p<0.0001). TGFβ+ ML-7 inhibited the contraction to the level of w/o (p=0.0024), which was only 35% of ML-7 alone. In the contraction study the cells were terminated after 2 days of culture, thus prior to when biomarker of ECM remodeling is usually assessed. However, FBN-C was detectable and a significant release of fibronectin by TGFβ and PDGF compared to w/o was found in the supernatant (both p<0.0001). The gene expression of FBN was only increased with TGFβ (p<0.05) and not PDGF. ML-7 alone tended to decrease FBN-C and in combination with TGFβ the FBN level was significantly decreased compared to TGFβ alone (p<0.0001). However, the level of TGFβ+ML-7 was significantly higher than ML-7 alone (p=0.038).TGFβ increased the gene expression of most genes assessed, except Col6a1. PDGF increased the gene expression of Col3a1, Col5a1 and Col6a1 above the critical fold change of 2, but only significantly in Col5a1 and Col6a1 (both p<0.05).Conclusion:This study demonstrates that TGFβ and PDGF have different mechanical capacities in human healthy dermal fibroblasts; TGFβ increased gene expression of ECM related genes, such as collagens and have increased FBN release in the supernatant already 2 days after initial treatment. PDGF has increased contraction, proliferation and migratory capacities and less expression of ECM related genes and proteins.Disclosure of Interests:Anne Sofie Siebuhr Employee of: Nordic Bioscience, Sofie Falkenløve Madsen: None declared, Morten Karsdal Shareholder of: Nordic Bioscience A/S., Employee of: Full time employee at Nordic Bioscience A/S., Anne-Christine Bay-Jensen Shareholder of: Nordic Bioscience A/S, Employee of: Full time employee at Nordic Bioscience A/S., Pernille Juhl Employee of: Nordic Bioscience

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