Meta-Analysis of Joint Test of SNP and SNP-Environment Interaction with Heterogeneity

2021 ◽  
pp. 1-9
Author(s):  
Qinqin Jin ◽  
Gang Shi
Keyword(s):  
Meta Analysis ◽  
Likelihood Ratio Statistic ◽  
Random Effect ◽  
Random Effect Model ◽  
Environment Interaction ◽  
Nucleotide Polymorphisms ◽  
Group Level ◽  
Null Distributions ◽  
Level Data ◽  
Meta Regression

Many complex diseases are caused by single nucleotide polymorphisms (SNPs), environmental factors, and the interaction between SNPs and environment. Joint tests of the SNP and SNP-environment interaction effects (JMA) and meta-regression (MR) are commonly used to evaluate these SNP-environment interactions. However, these two methods do not consider genetic heterogeneity. We previously presented a random-effect MR, which provided higher power than the MR in datasets with high heterogeneity. However, this method requires group-level data, which sometimes are not available. Given this, we designed this study to evaluate the introduction of the random effects of SNP and SNP-environment interaction into the JMA, and then extended this to the random effect model. Likelihood ratio statistic is applied to test the JMA and the new method we proposed in this paper. We evaluated the null distributions of these tests, and the powers for this method. This method was verified by simulation and was shown to provide similar powers to the random effect meta-regression method (RMR). However, this method only requires study-level data which relaxed the condition of the RMR. Our study suggests that this method is more suitable for finding the association between SNP and diseases in the absence of group-level data.

scholarly journals Stage 2 Registered Report: Anomalous perception in a Ganzfeld condition - A meta-analysis of more than 40 years investigation

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 234
Author(s):  
Patrizio E. Tressoldi ◽  
Lance Storm
Keyword(s):  
Regression Model ◽  
Effect Size ◽  
Close Agreement ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Questionable Research Practices ◽  
Effect Model ◽  
Meta Regression ◽  
Stage 1

This meta-analysis is an investigation into anomalous perception (i.e., conscious identification of information without any conventional sensorial means). The technique used for eliciting an effect is the ganzfeld condition (a form of sensory homogenization that eliminates distracting peripheral noise). The database consists of studies published between January 1974 and December 2020 inclusive. The overall effect size estimated both with a frequentist and a Bayesian random-effect model, were in close agreement yielding an effect size of .088 (.04-.13). This result passed four publication bias tests and seems not contaminated by questionable research practices. Trend analysis carried out with a cumulative meta-analysis and a meta-regression model with Year of publication as covariate, did not indicate sign of decline of this effect size. The moderators analyses show that selected participants outcomes were almost three-times those obtained by non-selected participants and that tasks that simulate telepathic communication show a two-fold effect size with respect to tasks requiring the participants to guess a target. The Stage 1 Registered Report can be accessed here: https://doi.org/10.12688/f1000research.24868.3

scholarly journals Association between calcium-sensing receptor (CaSR) R990G, CaSR A986S, and CaSR Q1011E gene polymorphisms and the risk of urolithiasis: a meta-analysis

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Besut Daryanto ◽  
Basuki Bambang Purnomo ◽  
Atma Gunawan ◽  
Fredo Tamara ◽  
Saga Aditya Hutama ◽  
...  
Keyword(s):  
Gene Polymorphisms ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Group Analysis ◽  
Asian Population ◽  
Nucleotide Polymorphisms ◽  
Calcium Sensing Receptor ◽  
Casr Gene ◽  
Calcium Sensing

Abstract Backgrounds In the last two decades, studies have been widely carried out to assess the association between single-nucleotide polymorphisms (SNPs) of calcium-sensing receptor (CaSR) gene in exon 7 and the risk of urolithiasis. However, inconsistency across the studies was reported. Therefore, our current study aimed to perform a meta-analysis concerning the association between the risk of urolithiasis and the gene polymorphisms of CaSR R990G, CaSR A986S, and CaSR Q1011E. Methods Published papers from PubMed, Embase, Cohcrane, and Web of science were included for the study, and they were analyzed using fixed or random effect model. Results A total of 11 papers consisting of eight papers evaluating CaSR R990G, nine papers evaluating CaSR A986S, and five papers evaluating CaSR Q1011E were included in our analysis. Our pooled calculation found that protective effect against urolithiasis was observed in R allele and RR genotype of CaSR R990G and A allele and AA genotype of CaSR A986S. Conversely, increased susceptibility to urolithiasis was found in G allele and RG genotype of CaSR R990G and S allele of CaSR A986S. Interestingly, our findings in sub-group analysis confirmed that the correlation between CaSR R990G and urolithiasis was found in Caucasian population. Meanwhile, in Asian population, the association was observed in CaSR A986S. Conclusions CaSR R990G and CaSR A986S, but not CaSR Q1011E, are associated with the risk of urolithiasis.

scholarly journals Diabetes is associated with increased risk for in-hospital mortality in patients with COVID-19: a systematic review and meta-analysis comprising 18,506 patients

2020 ◽  
Author(s):  
Leonidas Palaiodimos ◽  
Natalia Chamorro-Pareja ◽  
Dimitrios Karamanis ◽  
Weijia Li ◽  
Phaedon D. Zavras ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Hospitalized Patients ◽  
Risk Of Death ◽  
Increased Risk ◽  
Patients With Diabetes ◽  
Meta Regression ◽  
Meta Regression Analysis

AbstractBackgroundInfectious diseases are more frequent and can be associated with worse outcomes in patients with diabetes. Our aim was to systematically review and synthesize with a meta-analysis the available observational studies reporting the effect of diabetes in mortality among hospitalized patients with COVID-19.MethodsMedline, Embase, Google Scholar, and medRxiv databases were reviewed. A random-effect model meta-analysis was used and I-square was utilized to assess the heterogeneity. In-hospital mortality was defined as the endpoint. Sensitivity, subgroup, and meta-regression analyses were performed.Results18,506 patients were included in this meta-analysis (3,713 diabetics and 14,793 non-diabetics). Patients with diabetes were associated with a higher risk of death compared to patients without diabetes (OR: 1.65; 95% CI: 1.35-1.96; I2 77.4%). The heterogeneity was high. A study level meta-regression analysis was performed for all the important covariates and no significant interactions were found between the covariates and the outcome of mortality.ConclusionThis meta-analysis shows that that the likelihood of death is 65% higher in diabetic hospitalized patients with COVID-19 compared to non-diabetics. Further studies are needed to assess whether this association is independent or not, as well as to investigate to role of glucose control prior or during the disease.

scholarly journals Socioeconomic Factors and Caries in People between 19 and 60 Years of Age: An Update of a Systematic Review and Meta-Analysis of Observational Studies

2018 ◽  
Vol 15 (8) ◽  
pp. 1775 ◽  
Author(s):  
Simone Costa ◽  
Carolina Martins ◽  
Mânia Pinto ◽  
Mara Vasconcelos ◽  
Mauro Abreu
Keyword(s):  
Systematic Review ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Socioeconomic Indicators ◽  
Effect Model ◽  
Statistical Heterogeneity ◽  
Newcastle Ottawa Scale ◽  
Meta Regression ◽  
Ottawa Scale

This study is aimed to perform an update of a systematic review and meta-regression to evaluate the effect modification of the socioeconomic indicators on caries in adults. We included studies that associated social determinants with caries, with no restriction of year and language. The Newcastle-Ottawa Scale was used to evaluate the risk of bias. With regard to the meta-analysis, statistical heterogeneity was evaluated by I2, and the random effect model was used when it was high. A subgroup analysis was conducted for socioeconomic indicators, and a meta-regression was performed. Publication bias was assessed through Egger’s test. Sixty-one studies were included in the systematic review and 25 were included in the meta-analysis. All of the studies were published between 1975 and 2016. The most frequent socioeconomic indicators were schooling, income, and socioeconomic status (SES). In the quantitative analysis, the DMFT (decayed, missing, filled teeth) variation was attributed to the studies’ heterogeneity. The increase of 10.35 units in the proportion of people with lower SES was associated with an increase of one unit in DMFT, p = 0.050. The findings provide evidence that populations with the highest proportions of people with low SES are associated with a greater severity of caries. The results suggest the need for actions to reduce the inequalities in oral health (PROSPERO [CRD42017074434]).

scholarly journals A Systematic Review, Meta-Analysis, and Meta-Regression Evaluating the Efficacy and Mechanisms of Action of Probiotics and Synbiotics in the Prevention of Surgical Site Infections and Surgery-Related Complications

2018 ◽  
Vol 7 (12) ◽  
pp. 556 ◽  
Author(s):  
Karolina Skonieczna-Żydecka ◽  
Mariusz Kaczmarczyk ◽  
Igor Łoniewski ◽  
Luis Lara ◽  
Anastasios Koulaouzidis ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Surgical Site Infections ◽  
Short Chain Fatty Acids ◽  
Cochrane Central Register ◽  
Reactive Protein ◽  
Central Register ◽  
Meta Regression ◽  
Meta Regression Analysis

Intestinal microbiota play an important role in the pathogenesis of surgical site infections (SSIs) and other surgery-related complications (SRCs). Probiotics and synbiotics were found to lower the risk of surgical infections and other surgery-related adverse events. We systematically reviewed the approach based on the administration of probiotics and synbiotics to diminish SSIs/SRCs rates in patients undergoing various surgical treatments and to determine the mechanisms responsible for their effectiveness. A systematic literature search in PubMed/MEDLINE/Cochrane Central Register of Controlled Trials from the inception of databases to June 2018 for trials in patients undergoing surgery supplemented with pre/pro/synbiotics and randomized to the intervention versus placebo/no treatment and reporting on primarily: (i) putative mechanisms of probiotic/symbiotic action, and secondarily (ii) SSIs and SRCs outcomes. Random-effect model meta-analysis and meta-regression analysis of outcomes was done. Thirty-five trials comprising 3028 adult patients were included; interventions were probiotics (n = 16) and synbiotics (n = 19 trials). We found that C-reactive protein (CRP) and Interleukin-6 (IL-6) were significantly decreased (SMD: −0.40, 95% CI [−0.79, −0.02], p = 0.041; SMD: −0.41, 95% CI [−0.70, −0.02], p = 0.006, respectively) while concentration of acetic, butyric, and propionic acids were elevated in patients supplemented with probiotics (SMD: 1.78, 95% CI [0.80, 2.76], p = 0.0004; SMD: 0.67, 95% CI [0.37, −0.97], p = 0.00001; SMD: 0.46, 95% CI [0.18, 0.73], p = 0.001, respectively). Meta-analysis confirmed that pro- and synbiotics supplementation was associated with significant reduction in the incidence of SRCs including abdominal distention, diarrhea, pneumonia, sepsis, surgery site infection (including superficial incisional), and urinary tract infection, as well as the duration of antibiotic therapy, duration of postoperative pyrexia, time of fluid introduction, solid diet, and duration of hospital stay (p < 0.05). Probiotics and synbiotics administration counteract SSIs/SRCs via modulating gut-immune response and production of short chain fatty acids.

scholarly journals Meta-Analysis on the Association of C-Reactive Protein Polymorphisms with Metabolic Syndrome

2020 ◽  
Vol 07 (01) ◽  
pp. 008-013
Author(s):  
Seyedeh Maryam Sharafi ◽  
Manijeh Mahdavi ◽  
Roya Riahi ◽  
Majid Kheirollahi ◽  
Roya Kelishadi
Keyword(s):  
Metabolic Syndrome ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
P Value ◽  
Significant Heterogeneity ◽  
Nucleotide Polymorphisms ◽  
C Reactive Protein ◽  
Cross Sectional ◽  
Reactive Protein

AbstractPolymorphisms in the C-reactive protein (CRP) genes might have crucial role in the development of metabolic syndrome (MetS). In the current comprehensive meta-analyses, we aim to provide a quantitative assessment of the association between CRP single-nucleotide polymorphisms (SNPs) and the risk of MetS. An electronic search was performed on several databases. After data extraction, random effect model was used to calculate the pooled odds ratio (OR) and 95% confidence intervals (CIs). Four independent studies including case–control, cohort, and cross-sectional methods were analyzed. Our meta-analysis indicated that CRP polymorphisms are not significantly associated with MetS (OR = 0.92, 95% CI = 0.77–1.10) with significant heterogeneity (I 2 = 55.4%; p-value = 0.008). The subgroup analysis revealed that only GG has significant association with MetS (OR = 0.32, 95% CI = 0.13–0.80, p-value = 0.015) without significant heterogeneity (I 2 = 0%, p-value > 0.05). In conclusion, this meta-analysis provides strong evidence that only some SNPs of CRP gene are associated with the risk for development of MetS; and this relationship does not exist in different ethnic populations.

scholarly journals Meta-analysis of SNP-environment interaction with heterogeneity for overlapping data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qinqin Jin ◽  
Gang Shi
Keyword(s):  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Type I ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Overlapping Data ◽  
Effect Model

AbstractMeta-analysis is a popular method used in genome-wide association studies, by which the results of multiple studies are combined to identify associations. This process generates heterogeneity. Recently, we proposed a random effect model meta-regression method (MR) to study the effect of single nucleotide polymorphism (SNP)-environment interactions. This method takes heterogeneity into account and produces high power. We also proposed a fixed effect model overlapping MR in which the overlapping data is taken into account. In the present study, a random effect model overlapping MR that simultaneously considers heterogeneity and overlapping data is proposed. This method is based on the random effect model MR and the fixed effect model overlapping MR. A new way of solving the logarithm of the determinant of covariance matrices in likelihood functions is also provided. Tests for the likelihood ratio statistic of the SNP-environment interaction effect and the SNP and SNP-environment joint effects are given. In our simulations, null distributions and type I error rates were proposed to verify the suitability of our method, and powers were applied to evaluate the superiority of our method. Our findings indicate that this method is effective in cases of overlapping data with a high heterogeneity.

scholarly journals Meta-analysis on maternal deaths and assessing significant factors for heterogeneity between states of India during 2016

2021 ◽  
Vol 10 (8) ◽  
pp. 3192
Author(s):  
Vanamail Perumal
Keyword(s):  
Maternal Mortality ◽  
Meta Analysis ◽  
Random Effect ◽  
Maternal Mortality Ratio ◽  
Random Effect Model ◽  
Registration System ◽  
Mortality Ratio ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Significant Factors

Objective of the study was to provide a more precise estimate of maternal mortality (MM), maternal mortality ratio (MMR) and to identify significant factors contributing for heterogeneity between the states in India. “Metaprop” procedure in STATA software, which are specific to binomial data was applied on state wise MM data published by sample registration system (SRS) during 2014-16. An overall MM estimate and potential sources of heterogeneity could be identified using meta-regression. Corrected estimates of MMR by states were compared. SRS published the MM data by 17 Major states. Overall reported MM was 8.8 per 100, 000 women. Estimate obtained by random effect model was 8.3 (95% CI: 5.9-11.1) per 100,000 women. Heterogeneity between states was very high (I2-statistics =91.9%), and egger regression revealed no reporting bias (p=0.672). Meta-regression analysis indicated that the percent women attending full antenatal care (ANC) visits found to be highly significant (p<0.001) for MM with inverse relationship implying that the states with a higher percentage of women with full ANC visits are likely to have lesser MM. While the estimate of MMR by SRS was 130 per 100,000 live births, corrected MMR was 123 (95% CI: 87-164) accounting for 26% reduction from previous estimate 167 obtained in 2013. This paper provided a precious estimate of both MM and MMR adjusted for sampling weight. Further, the importance of either full ANC visits or four ANC visits could be demonstrated for reduction in MMR on achieving the Millennium development goal (MDG) in the country. 

scholarly journals Stage 1 Registered Report: Anomalous perception in a Ganzfeld condition - A meta-analysis of more than 40 years investigation

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 826
Author(s):  
Patrizio E. Tressoldi ◽  
Lance Storm
Keyword(s):  
Regression Model ◽  
Trend Analysis ◽  
Effect Size ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Effect Model ◽  
Meta Regression ◽  
Level Of Experience ◽  
Stage 1

This meta-analysis is an investigation into anomalous perception (i.e., conscious identification of information without any conventional sensorial means). The technique used for eliciting an effect is the ganzfeld condition (a form of sensory homogenization that eliminates distracting peripheral noise). The database consists of peer-reviewed studies published between January 1974 and June 2020 inclusive. The overall effect size will be estimated using a frequentist and a Bayesian random-effect model. Moderators analyses will be used to examine the influence of level of experience of participants, the type of task and the peer-review level. Publication bias will be estimated by using four different tests. Trend analysis will be conducted with a cumulative meta-analysis and a meta-regression model with Year of publication as covariate.

scholarly journals Stage 1 Registered Report: Anomalous perception in a Ganzfeld condition - A meta-analysis of more than 40 years investigation

F1000Research ◽  
2021 ◽  
Vol 9 ◽  
pp. 826 ◽  
Author(s):  
Patrizio E. Tressoldi ◽  
Lance Storm
Keyword(s):  
Regression Model ◽  
Trend Analysis ◽  
Effect Size ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Effect Model ◽  
Meta Regression ◽  
Level Of Experience ◽  
Stage 1

This meta-analysis is an investigation into anomalous perception (i.e., conscious identification of information without any conventional sensorial means). The technique used for eliciting an effect is the ganzfeld condition (a form of sensory homogenization that eliminates distracting peripheral noise). The database consists of peer-reviewed studies published between January 1974 and June 2020 inclusive. The overall effect size will be estimated using a frequentist and a Bayesian random-effect model. Moderators analyses will be used to examine the influence of level of experience of participants, the type of task and the peer-review level. Publication bias will be estimated by using four different tests. Trend analysis will be conducted with a cumulative meta-analysis and a meta-regression model with Year of publication as covariate.

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