scholarly journals Analytical and numerical comparisons of two methods of estimation of additive × additive interaction of QTL effects

2012 ◽  
Vol 69 (4) ◽  
pp. 240-246 ◽  
Author(s):  
Jan Bocianowski
Keyword(s):  
Additive Interaction ◽  
Numerical Comparisons ◽  
Qtl Effects

scholarly journals Analytical and numerical comparisons of two methods of estimation of additive × additive × additive interaction of QTL effects

2021 ◽  
Author(s):  
Adrian Cyplik ◽  
Jan Bocianowski
Keyword(s):  
Molecular Marker ◽  
Doubled Haploid ◽  
Numerical Comparison ◽  
Additive Interaction ◽  
Numerical Comparisons ◽  
Plant Phenotype ◽  
Dh Lines ◽  
Qtl Effects

AbstractThis paper presents the analytical and numerical comparison of two methods of estimation of additive × additive × additive (aaa) interaction of QTL effects. The first method takes into account only the plant phenotype, while in the second we also included genotypic information from molecular marker observation. Analysis was made on 150 doubled haploid (DH) lines of barley derived from cross Steptoe × Morex and 145 DH lines from Harrington × TR306 cross. In total, 153 sets of observation was analyzed. In most cases, aaa interactions were found with an exert effect on QTL. Results also show that with molecular marker observations, obtained estimators had smaller absolute values than phenotypic estimators.

PHOSPHO1 Gene DNA Methylations are Associated with a Change in HDL-C Response to Simvastatin Treatment

2020 ◽  
Vol 26 (38) ◽  
pp. 4944-4952 ◽  
Author(s):  
Juanlin Fan ◽  
Qianru Cai ◽  
Di Zhang ◽  
Justin Weinstock ◽  
Xiaoxiao Qu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Density Lipoprotein ◽  
Significant Negative Correlation ◽  
High Response ◽  
Lipid Lowering ◽  
Additive Interaction ◽  
Simvastatin Treatment ◽  
Obese Subjects ◽  
Dna Methylations ◽  
Response Group

Objective: Our aim was to detect the effects of DNA methylations in the phosphoethanolamine/ phosphocholine phosphatase (PHOSPHO1) gene on the therapeutic efficacy of simvastatin. Methods: We used an extreme sampling approach by selecting 211 individuals from approximately the top and bottom 15% of adjusted lipid-lowering response residuals to simvastatin (n=104 for the high response group and n=107 for the low response group) from a total of 734 subjects with hyperlipidemia. They received a daily oral dose of 20 mg simvastatin for eight consecutive weeks. DNA methylation loci at the PHOSPHO1 gene were measured using high-throughput next-generation sequencing-based sequencing technology. Fasting serum lipids were measured at baseline and after eight weeks of simvastatin treatment. Results: Mean PHOSPHO1 DNA methylation had a significant negative correlation with high-density lipoprotein cholesterol (HDL-C) variation (β=-0.014, P=0.045) in the high response group. After stratifying by body mass index (BMI), the associations between the PHOSPHO1 DNA methylations and the change in HDL-C in response to simvastatin were more significant in obese subjects with a BMI of 25 kg/m2 or higher (β=-0.027, P=0.002). Mean PHOSPHO1 methylation and traditional predictors could explain up to 24.7% (adjusted R2) of the change in HDL-C response in obese patients. There was a statistically significant additive interaction term (P=0.028) between BMI and mean PHOSPHO1 methylation in the model of the change in HDL-C in response to simvastatin. Conclusion: Our findings suggest that PHOSPHO1 DNA methylations are associated with a change in HDL-C in response to simvastatin treatment, and this association is especially dependent on the extent of patient obesity.

Accuracy and sensitivity of different Bayesian methods for genomic prediction using simulation and real data

2020 ◽  
Vol 19 (3) ◽  
Author(s):  
Saheb Foroutaifar
Keyword(s):  
Data Analysis ◽  
Bayesian Methods ◽  
Milk Fat ◽  
Prediction Accuracy ◽  
Real Data ◽  
Fat Percentage ◽  
Real Data Analysis ◽  
Wide Range ◽  
High Heritability ◽  
Qtl Effects

AbstractThe main objectives of this study were to compare the prediction accuracy of different Bayesian methods for traits with a wide range of genetic architecture using simulation and real data and to assess the sensitivity of these methods to the violation of their assumptions. For the simulation study, different scenarios were implemented based on two traits with low or high heritability and different numbers of QTL and the distribution of their effects. For real data analysis, a German Holstein dataset for milk fat percentage, milk yield, and somatic cell score was used. The simulation results showed that, with the exception of the Bayes R, the other methods were sensitive to changes in the number of QTLs and distribution of QTL effects. Having a distribution of QTL effects, similar to what different Bayesian methods assume for estimating marker effects, did not improve their prediction accuracy. The Bayes B method gave higher or equal accuracy rather than the rest. The real data analysis showed that similar to scenarios with a large number of QTLs in the simulation, there was no difference between the accuracies of the different methods for any of the traits.

scholarly journals Household mold exposure interacts with inflammation-related genetic variants on childhood asthma: a case–control study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yu Zhang ◽  
Li Hua ◽  
Quan-Hua Liu ◽  
Shu-Yuan Chu ◽  
Yue-Xin Gan ◽  
...  
Keyword(s):  
Childhood Asthma ◽  
Case Control Study ◽  
Additive Model ◽  
Case Control ◽  
Nucleotide Polymorphisms ◽  
Additive Interaction ◽  
Asthmatic Children ◽  
Gene Environment ◽  
Mold Exposure ◽  
Control Study

Abstract Background A number of studies have examined the association between mold exposure and childhood asthma. However, the conclusions were inconsistent, which might be partly attributable to the lack of consideration of gene function, especially the key genes affecting the pathogenesis of childhood asthma. Research on the interactions between genes and mold exposure on childhood asthma is still very limited. We therefore examined whether there is an interaction between inflammation-related genes and mold exposure on childhood asthma. Methods A case–control study with 645 asthmatic children and 910 non-asthmatic children aged 3–12 years old was conducted. Eight single nucleotide polymorphisms (SNPs) in inflammation-related genes were genotyped using MassARRAY assay. Mold exposure was defined as self-reported visible mold on the walls. Associations between visible mold exposure, SNPs and childhood asthma were evaluated using logistic regression models. In addition, crossover analyses were used to estimate the gene-environment interactions on childhood asthma on an additive scale. Results After excluding children without information on visible mold exposure or SNPs, 608 asthmatic and 839 non-asthmatic children were included in the analyses. Visible mold exposure was reported in 151 asthmatic (24.8%) and 119 non-asthmatic children (14.2%) (aOR 2.19, 95% CI 1.62–2.97). The rs7216389 SNP in gasdermin B gene (GSDMB) increased the risk of childhood asthma with each C to T substitution in a dose-dependent pattern (additive model, aOR 1.32, 95% CI 1.11–1.57). Children carrying the rs7216389 T allele and exposed to visible mold dramatically increased the risk of childhood asthma (aOR 3.21; 95% CI 1.77–5.99). The attributable proportion due to the interaction (AP: 0.47, 95% CI 0.03–0.90) and the relative excess risk due to the interaction (RERI: 1.49, 95% CI 0–2.99) were statistically significant. Conclusions In the present study, there was a significant additive interaction between visible mold exposure and rs7216389 SNP on childhood asthma. Future studies need to consider the gene-environment interactions when exploring the risk factors of childhood asthma.

scholarly journals The risk of preterm birth in combinations of mental disorder and socioeconomic position among Danish women

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
C K Knudsen ◽  
A M S Christensen ◽  
S Heuckendorff ◽  
K Fonager ◽  
C Overgaard
Keyword(s):  
Mental Health ◽  
Preterm Birth ◽  
Socioeconomic Position ◽  
Educational Level ◽  
Lower Degree ◽  
Health Conditions ◽  
Additive Interaction ◽  
Educational Levels ◽  
Mental Health Conditions ◽  
First Time

Abstract Background Inequality in preterm birth is a public health challenge requiring identification of pregnant women at particularly high risk of preterm birth. Therefore, the aim was to estimate the risk of preterm birth in women with different combinations of mental health conditions and socioeconomic position. Methods Based on Danish registries, we conducted a nationwide cohort study including all first-time mothers giving birth to a singleton liveborn infant in Denmark between 2000 through 2016. We examined the risk of preterm birth (<37 weeks of gestation) in different combinations of mental health conditions (no, minor, and moderate/severe) and educational level (high, intermediate, and low) in three age strata (<25, 25-30, and >30 years). The relative risk of preterm birth was estimated using Poisson regression with a robust error variance. We measured the attributable proportion to assess additive interaction between the effects of exposures. Results Of the 415,523 included first time mothers, 29,069 (7,0%) gave birth preterm. The risk of preterm birth increased in combinations of higher degree of mental health conditions, lower degree of educational level, and increasing age. Women aged>30 years with moderate/severe mental health conditions and low educational level had the highest risk of preterm birth (13.7%). The analysis of additive interaction revealed only a limited additional effect of being exposed to mental health conditions and lower educational levels in each age strata. However, positive additive interaction was found between age>30 year and combinations of mental health conditions and educational level. Conclusions Substantial inequality in preterm birth remains with increasing risk in women with combinations of higher degree of mental health conditions and lower degree of educational level. In the prevention of inequality in preterm birth special attention on women aged>30 years exposed to mental health conditions and lower educational levels is essential

scholarly journals Integration and Modularity of Quantitative Trait Locus Effects on Geometric Shape in the Mouse Mandible

Genetics ◽  
2004 ◽  
Vol 166 (4) ◽  
pp. 1909-1921
Author(s):  
Christian Peter Klingenberg ◽  
Larry J Leamy ◽  
James M Cheverud
Keyword(s):  
Quantitative Trait ◽  
Parametric Bootstrap ◽  
Interval Mapping ◽  
Procrustes Analysis ◽  
Bootstrap Test ◽  
Mandible Shape ◽  
Trait Locus ◽  
F2 Generation ◽  
Analysis Interval ◽  
Qtl Effects

Abstract The mouse mandible has long served as a model system for complex morphological structures. Here we use new methodology based on geometric morphometrics to test the hypothesis that the mandible consists of two main modules, the alveolar region and the ascending ramus, and that this modularity is reflected in the effects of quantitative trait loci (QTL). The shape of each mandible was analyzed by the positions of 16 morphological landmarks and these data were analyzed using Procrustes analysis. Interval mapping in the F2 generation from intercrosses of the LG/J and SM/J strains revealed 33 QTL affecting mandible shape. The QTL effects corresponded to a variety of shape changes, but ordination or a parametric bootstrap test of clustering did not reveal any distinct groups of QTL that would affect primarily one module or the other. The correlations of landmark positions between the two modules tended to be lower than the correlations between arbitrary subsets of landmarks, indicating that the modules were relatively independent of each other and confirming the hypothesized location of the boundary between them. While these results are in agreement with the hypothesis of modularity, they also underscore that modularity is a question of the relative degrees to which QTL contribute to different traits, rather than a question of discrete sets of QTL contributing to discrete sets of traits.

Additive interaction between scopolamine and nitric oxide agents on immobility in the forced swim test but not exploratory activity in the hole-board

2019 ◽  
Vol 236 (11) ◽  
pp. 3353-3362 ◽  
Author(s):  
Mohammad Nasehi ◽  
Mohammad-Hossein Mohammadi-Mahdiabadi-Hasani ◽  
Mohaddeseh Ebrahimi-Ghiri ◽  
Mohammad-Reza Zarrindast
Keyword(s):  
Nitric Oxide ◽  
Forced Swim Test ◽  
Exploratory Activity ◽  
Additive Interaction ◽  
Swim Test ◽  
Forced Swim ◽  
Hole Board

scholarly journals Mortality Outcomes in People Experiencing Homelessness Across England: a population-based study

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
D Menezes ◽  
D Lewer ◽  
A Yavlinsky ◽  
M Tinelli ◽  
R Aldridge
Keyword(s):  
Hospital Discharge ◽  
Mortality Risk ◽  
Meta Analysis ◽  
Population Based ◽  
Mortality Data ◽  
Additive Interaction ◽  
Population Based Study ◽  
Group A ◽  
Healthcare Interventions ◽  
Discharge From Hospital

Abstract Introduction The number of people experiencing homelessness in England has increased since 2010 and a recent systematic review and meta-analysis demonstrated high levels of mortality in this group across high-income countries. In this study we examine the death rates in people experiencing homelessness after discharge from hospital. Methods This is a study of linked hospital admission records and mortality data for two groups. First, a “Homeless group”: people seen by 17 specialist homeless discharge schemes between 1 November 2013 and 30 November 2016. Second, an “IMD5 group”: A matched group of patients who live in deprived areas and have the same age and sex, and were discharged from the same hospital in the same year as the homeless patient. Our analysis entailed calculating mortality rates across each group and by the number of comorbidities. Results The mortality rate for the IMD5 group was 1,935 deaths per 100,000 person years, compared with 5,691 for the homeless group, giving a rate ratio of 2.9 (95% CI 2.5-3.5). The mortality risk increased with the number of comorbidities. Individuals in the IMD5 group with zero comorbidities had a death rate of 831 per 100,000 person-years, compared with the homeless group for which the corresponding figure was 2,598 and or those with 4+ comorbidities were 7,324 (IMD5) and 12,714 (homeless). This suggests a 'super-additive' interaction in which the effect of morbidity on mortality risk after discharge is greater for homeless patients. Survival at 5 years for the homelessness group was for men 80% (95% CI 77-85) and women 85 (95% CI 81-87). Conclusions This study shows that the well-established inequity in mortality for people experiencing homelessness exists after discharge from hospital and is greatest for the most unwell patients. Our results suggest a need for greater emphasis on prevention of homelessness, early healthcare interventions and improved hospital discharge arrangements for this population. Key messages The well-established inequity in mortality for people experiencing homelessness exists after discharge from hospital and is greatest for the most unwell patients. Our results suggest a need for greater emphasis on prevention of homelessness, early healthcare interventions and improved hospital discharge arrangements for this population.

Genetic and Nongenetic Bases for the L-Shaped Distribution of Quantitative Trait Loci Effects

Genetics ◽  
2001 ◽  
Vol 157 (4) ◽  
pp. 1773-1787 ◽  
Author(s):  
Bruno Bost ◽  
Dominique de Vienne ◽  
Frédéric Hospital ◽  
Laurence Moreau ◽  
Christine Dillmann
Keyword(s):  
Linkage Disequilibrium ◽  
Quantitative Trait Loci ◽  
Population Size ◽  
Quantitative Trait ◽  
Metabolic Flux ◽  
Genetic Model ◽  
Small Population ◽  
Additive Genetic Model ◽  
Metabolic Mechanism ◽  
Qtl Effects

Abstract The L-Shaped distribution of estimated QTL effects (R2) has long been reported. We recently showed that a metabolic mechanism could account for this phenomenon. But other nonexclusive genetic or nongenetic causes may contribute to generate such a distribution. Using analysis and simulations of an additive genetic model, we show that linkage disequilibrium between QTL, low heritability, and small population size may also be involved, regardless of the gene effect distribution. In addition, a comparison of the additive and metabolic genetic models revealed that estimates of the QTL effects for traits proportional to metabolic flux are far less robust than for additive traits. However, in both models the highest R2's repeatedly correspond to the same set of QTL.

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