scholarly journals Mediation model with a categorical exposure and a censored mediator with application to a genetic study

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0257628
Author(s):  
Jian Wang ◽  
Jing Ning ◽  
Sanjay Shete
Keyword(s):  
Genetic Variants ◽  
Genetic Model ◽  
Mediating Effect ◽  
Outcome Variable ◽  
Simulation Studies ◽  
Mediation Model ◽  
Genetic Studies ◽  
Age At Menopause ◽  
Empirical Performance

Mediation analysis is a statistical method for evaluating the direct and indirect effects of an exposure on an outcome in the presence of a mediator. Mediation models have been widely used to determine direct and indirect contributions of genetic variants in clinical phenotypes. In genetic studies, the additive genetic model is the most commonly used model because it can detect effects from either recessive or dominant models (or any model in between). However, the existing approaches for mediation model cannot be directly applied when the genetic model is additive (e.g. the most commonly used model for SNPs) or categorical (e.g. polymorphic loci), and thus modification to measures of indirect and direct effects is warranted. In this study, we proposed overall measures of indirect, direct, and total effects for a mediation model with a categorical exposure and a censored mediator, which accounts for the frequency of different values of the categorical exposure. The proposed approach provides the overall contribution of the categorical exposure to the outcome variable. We assessed the empirical performance of the proposed overall measures via simulation studies and applied the measures to evaluate the mediating effect of a women’s age at menopause on the association between genetic variants and type 2 diabetes.

scholarly journals Estimation of indirect effect when the mediator is a censored variable

2017 ◽  
Vol 27 (10) ◽  
pp. 3010-3025 ◽  
Author(s):  
Jian Wang ◽  
Sanjay Shete
Keyword(s):  
Censored Data ◽  
Indirect Effect ◽  
Indirect Effects ◽  
Failure Time ◽  
Fasting Glucose ◽  
Accelerated Failure Time Model ◽  
Outcome Variable ◽  
Mediation Model ◽  
Time Model ◽  
Age At Menopause

A mediation model explores the direct and indirect effects of an initial variable ( X) on an outcome variable ( Y) by including a mediator ( M). In many realistic scenarios, investigators observe censored data instead of the complete data. Current research in mediation analysis for censored data focuses mainly on censored outcomes, but not censored mediators. In this study, we proposed a strategy based on the accelerated failure time model and a multiple imputation approach. We adapted a measure of the indirect effect for the mediation model with a censored mediator, which can assess the indirect effect at both the group and individual levels. Based on simulation, we established the bias in the estimations of different paths (i.e. the effects of X on M [ a], of M on Y [ b] and of X on Y given mediator M [ c’]) and indirect effects when analyzing the data using the existing approaches, including a naïve approach implemented in software such as Mplus, complete-case analysis, and the Tobit mediation model. We conducted simulation studies to investigate the performance of the proposed strategy compared to that of the existing approaches. The proposed strategy accurately estimates the coefficients of different paths, indirect effects and percentages of the total effects mediated. We applied these mediation approaches to the study of SNPs, age at menopause and fasting glucose levels. Our results indicate that there is no indirect effect of association between SNPs and fasting glucose level that is mediated through the age at menopause.

scholarly journals Estimating Genetic Inheritance in Case-control Studies

2019 ◽  
Author(s):  
Na Li ◽  
Jiayan Zhu ◽  
Zhengbang Li
Keyword(s):  
Genetic Variants ◽  
Genetic Model ◽  
Case Control ◽  
New Method ◽  
Nucleotide Polymorphisms ◽  
Case Control Studies ◽  
Single Nucleotide ◽  
Hardy Weinberg Equilibrium ◽  
Equilibrium Test

AbstractCase-control genetic association study is an efficient tool to search for the deleterious genetic variants predispose to human complex diseases, where the additive mode of inheritance is commonly assumed. However, how the genetic variants influence the occurrence of a certain disease is impossible to know beforehand. We show numerically that the existing procedures using the Hardy-Weinberg equilibrium test to choose the genetic model might be inconsistent. We propose a new method to choose the genetic model by adopting co-dominant code for risk allele and logistic regression model. Extensive computer simulation results demonstrate superiorities of the new method. Applications to six single nucleotide polymorphisms(SNPs) for breast cancer and eight SNPs for Type 2 Diabetes further show good performances of proposed method. In order to specify a genetic model for an allele, our method has some merits and is consistent as sample size is large. We propose to apply our method in related fields.

scholarly journals Effects of Genetic Variants of Nuclear Receptor Y on the Risk of Type 2 Diabetes Mellitus

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Ying Wang ◽  
Shanshan Yang ◽  
Qiuyue Guan ◽  
Jinglu Chen ◽  
Xueping Zhang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Genetic Variants ◽  
Genetic Model ◽  
Genotypic Frequency ◽  
Nucleotide Polymorphisms ◽  
Healthy Individuals ◽  
Chinese Han

Nuclear factor-Y (NF-Y) consists of three evolutionary conserved subunits including NF-YA, NF-YB, and NF-YC; it is a critical transcriptional regulator of lipid and glucose metabolism and adipokine biosynthesis that are associated with type 2 diabetes mellitus (T2DM) occurrence, while the impacts of genetic variants in the NF-Y gene on the risk of T2DM remain to be investigated. In the present study, we screened five single-nucleotide polymorphisms (SNPs) with the SNaPshot method in 427 patients with T2DM and 408 healthy individuals. Subsequently, we analyzed the relationships between genotypes and haplotypes constructed from these SNPs with T2DM under diverse genetic models. Furthermore, we investigated the allele effects on the quantitative metabolic traits. Of the five tagSNPs, we found that three SNPs (rs2268188, rs6918969, and rs28869187) exhibited nominal significant differences in allelic or genotypic frequency between patients with T2DM and healthy individuals. The minor alleles G, C, and C at rs2268188, rs6918969, and rs28869187, respectively, conferred a higher T2DM risk under a dominant genetic model, and the carriers of these risk alleles (either homozygotes of the minor allele or heterozygotes) had statistically higher levels of fasting plasma glucose, cholesterol, and triglycerides. Haplotype analysis showed that SNPs rs2268188, rs6918969, rs28869187, and rs35105472 formed a haplotype block, and haplotype TTAC was protective against T2DM (OR=0.76, 95% CI=0.33-0.82, P=0.004), while haplotype GCCG was associated with an elevated susceptibility to T2DM (OR=2.33, 95% CI=1.43-3.57, P=0.001). This study is the first ever observation to our knowledge that indicates the genetic variants of NF-YA might influence a Chinese Han individual’s occurrence of T2DM.

110-OR: Type 2 Diabetes (T2D)–Associated TCF7L2 Genetic Variants and Indices of Insulin Secretion and Sensitivity in Individuals at Risk for Type 1 Diabetes (T1D)

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 110-OR
Author(s):  
MARIA J. REDONDO ◽  
MEGAN V. WARNOCK ◽  
LAURA E. BOCCHINO ◽  
SUSAN GEYER ◽  
ALBERTO PUGLIESE ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
At Risk ◽  
Type 1 Diabetes ◽  
Insulin Secretion ◽  
Genetic Variants

Structural Mediation Model of Information System and Sustainable Performance of UAE Manufacturing Sector

2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Mohamed Ahmed Darwish Abdulla Larii ◽  
◽  
Fatma Ahmed Lari ◽  
Mohamed Ahmed Darwish Abdulla Lari ◽  
◽  
...  
Keyword(s):  
Information System ◽  
Manufacturing Sector ◽  
Organisational Culture ◽  
The Body ◽  
Mediating Effect ◽  
Operational Performance ◽  
Manufacturing Companies ◽  
Mediation Model ◽  
Sustainable Performance ◽  
The Relationship

This study intends to find out the mediating effect of organisational culture on the relationship between information system and sustainable performance of manufacturing sector in UAE. This study used AMOS-SEM software to develop mediation model that linking the mediating relationships between Information System, Organisational Culture and Sustainable operation Performance. Data was collected through questionnaire survey among the operation staff of Abu Dhabi manufacturing companies. A total 250 questionnaires were distributed however 205 were returned and only 200 are valid which indicates a response rate of 80%. The analysis found that TPS has positive but not significant effect to SP; OIS has positive but not significant effect to SP; FMW has a positive and significant effect on SP; SDS has a negative and not significant effect to SP and SP has positive but not significant effect OC. For the path relationship between the four exogenous variables (TPS, OIS, SDS, and FMW) and the mediator variable (OC), the results are TPS has positive and significant effect to OC; OIS has positive but not significant effect to OC; FMW has positive and significant effect to OC and SDS has positive and not significant effect to OC. Collectively, the five exogenous constructs (TPS, OIS, SDS, FMW and OC) explained 89% variation in operational performance and 86% of the variation in organisational culture. However, for a mediator, it was found that OC has no significant mediating effect on the relationship between TPS and SP; OC has no significant mediating effect on the relationship between OIS and SP; OC has no significant mediating effect on the relationship between SDS and SP and OC has no significant mediating effect on the relationship between FMW and SP. it can be concluded that there is a positive relationship between information system dimensions and operational performance. However organizational culture has no contributing any mediating effect to the relationship. These findings have contributed to the body of knowledge and could be shared among the UAE manufacturing practitioners.

The effect of proprioceptive training on postural control in people with diabetes: A randomized clinical trial comparing delivery at home, under supervision, or no training

2021 ◽  
pp. 026921552198901
Author(s):  
Nathalia Cristina de Souza Borges ◽  
Ariane Hidalgo Mansano Pletsch ◽  
Mariana Barbosa Buzato ◽  
Natalia Akemi Yamada Terada ◽  
Fernanda Maria Ferreira da Cruz ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Postural Control ◽  
Force Plate ◽  
Outcome Variable ◽  
Control Group ◽  
Functional Tests ◽  
Supervised Training ◽  
Proprioceptive Training ◽  
Home Training

Objective: Analyze postural control in the bipedal position as well as during gait and functional tests in patients with type 2 diabetes mellitus after supervised and unsupervised proprioceptive training. Design: A three-group randomized controlled trial. Setting: Physiotherapeutic Resources Lab, Department of Health Sciences, Ribeirão Preto Medical School, University of São Paulo Subjects: Eighty patients with type 2 diabetes allocated to three groups: control, home training, and supervised training. Interventions: The supervised and home training groups performed two weekly sessions of proprioceptive exercises for 12 weeks. The control group was not submitted to any of treatment. Main measures: Bipedal balance, gait, and performance on functional tests were evaluated before and after 12 weeks using the Balance Evaluation Systems Test (BESTest) and the force plate. Results: No significant improvements were found regarding postural control, gait, or performance on the functional tests, as evidenced by the inter-group comparisons of the total BESTest score [control: 90.7 (81.5–92.6); home training: 85.2 (77.8–90.3); supervised training: 88.4 (82.6–91.4), P > 0.05] as well as the tests performed on the force plate ( P > 0.05). The clinical effect size of the proposed intervention was less than 0.2, demonstrating no effect for the main outcome variable evaluated by the “Sensory Orientation” item of the BESTest and by the mCTSIB (pressure plate). Conclusions: The proposed proprioceptive training did not lead to improvements in postural control in patients with type 2 diabetes with no clinical signs of diabetic distal polyneuropathy when analyzed using the BESTest clinical evaluation and a force plate. Trial registration: NCT01861392 (clinicaltrials.gov).

scholarly journals A comprehensive evaluation of methods for Mendelian randomization using realistic simulations and an analysis of 38 biomarkers for risk of type 2 diabetes

2021 ◽  
Author(s):  
Guanghao Qi ◽  
Nilanjan Chatterjee
Keyword(s):  
Type 2 Diabetes ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Real Data ◽  
Causal Effects ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Simulation Studies ◽  
Sample Sizes

Abstract Background Previous studies have often evaluated methods for Mendelian randomization (MR) analysis based on simulations that do not adequately reflect the data-generating mechanisms in genome-wide association studies (GWAS) and there are often discrepancies in the performance of MR methods in simulations and real data sets. Methods We use a simulation framework that generates data on full GWAS for two traits under a realistic model for effect-size distribution coherent with the heritability, co-heritability and polygenicity typically observed for complex traits. We further use recent data generated from GWAS of 38 biomarkers in the UK Biobank and performed down sampling to investigate trends in estimates of causal effects of these biomarkers on the risk of type 2 diabetes (T2D). Results Simulation studies show that weighted mode and MRMix are the only two methods that maintain the correct type I error rate in a diverse set of scenarios. Between the two methods, MRMix tends to be more powerful for larger GWAS whereas the opposite is true for smaller sample sizes. Among the other methods, random-effect IVW (inverse-variance weighted method), MR-Robust and MR-RAPS (robust adjust profile score) tend to perform best in maintaining a low mean-squared error when the InSIDE assumption is satisfied, but can produce large bias when InSIDE is violated. In real-data analysis, some biomarkers showed major heterogeneity in estimates of their causal effects on the risk of T2D across the different methods and estimates from many methods trended in one direction with increasing sample size with patterns similar to those observed in simulation studies. Conclusion The relative performance of different MR methods depends heavily on the sample sizes of the underlying GWAS, the proportion of valid instruments and the validity of the InSIDE assumption. Down-sampling analysis can be used in large GWAS for the possible detection of bias in the MR methods.

scholarly journals Systemic Metabolic Alterations Correlate with Islet-Level Prostaglandin E2 Production and Signaling Mechanisms That Predict β-Cell Dysfunction in a Mouse Model of Type 2 Diabetes

Metabolites ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 58 ◽  
Author(s):  
Michael D. Schaid ◽  
Yanlong Zhu ◽  
Nicole E. Richardson ◽  
Chinmai Patibandla ◽  
Irene M. Ong ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Prostaglandin E2 ◽  
Genetic Model ◽  
Cell Mass ◽  
Arachidonic Acid Metabolite ◽  
Β Cell ◽  
Human Organ ◽  
Cell Dysfunction ◽  
Primary Mouse

The transition from β-cell compensation to β-cell failure is not well understood. Previous works by our group and others have demonstrated a role for Prostaglandin EP3 receptor (EP3), encoded by the Ptger3 gene, in the loss of functional β-cell mass in Type 2 diabetes (T2D). The primary endogenous EP3 ligand is the arachidonic acid metabolite prostaglandin E2 (PGE2). Expression of the pancreatic islet EP3 and PGE2 synthetic enzymes and/or PGE2 excretion itself have all been shown to be upregulated in primary mouse and human islets isolated from animals or human organ donors with established T2D compared to nondiabetic controls. In this study, we took advantage of a rare and fleeting phenotype in which a subset of Black and Tan BRachyury (BTBR) mice homozygous for the Leptinob/ob mutation—a strong genetic model of T2D—were entirely protected from fasting hyperglycemia even with equal obesity and insulin resistance as their hyperglycemic littermates. Utilizing this model, we found numerous alterations in full-body metabolic parameters in T2D-protected mice (e.g., gut microbiome composition, circulating pancreatic and incretin hormones, and markers of systemic inflammation) that correlate with improvements in EP3-mediated β-cell dysfunction.

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