Gene-environment interactions and aging visual function: a classical twin study.

OBJECTIVE:
To elucidate the contribution of environmental versus genetic factors to the significant losses in visual function associated with normal aging.
DESIGN:
A classical twin study.
PARTICIPANTS:
Forty-two twin pairs (21 monozygotic and 21 dizygotic; age 57-75 years) with normal visual acuity recruited through the Australian Twin Registry.
METHODS:
Cone function was evaluated by establishing absolute cone contrast thresholds to flicker (4 and 14 Hz) and isoluminant red and blue colors under steady state adaptation. Adaptation dynamics were determined for both cones and rods. Bootstrap resampling was used to return robust intrapair correlations for each parameter.
MAIN OUTCOME MEASURES:
Psychophysical thresholds and adaptational time constants.
RESULTS:
The intrapair correlations for all color and flicker thresholds, as well as cone absolute threshold, were significantly higher in monozygotic compared with dizygotic twin pairs (P<0.05). Rod absolute thresholds (P = 0.28) and rod and cone recovery rate (P = 0.83; P = 0.79, respectively) did not show significant differences between monozygotic and dizygotic twins in their intrapair correlations, indicating that steady-state cone thresholds and flicker thresholds have a marked genetic contribution, in contrast with rod thresholds and adaptive processes, which are influenced more by environmental factors over a lifetime.
CONCLUSIONS:
Genes and the environment contribute differently to important neuronal processes in the retina and the role they may play in the decline in visual function as we age. Consequently, retinal structures involved in rod thresholds and adaptive processes may be responsive to appropriate environmental manipulation. Because the functions tested are commonly impaired in the early stages of age-related macular degeneration, which is known to have a multifactorial etiology, this study supports the view that pathogenic pathways early in the disease may be altered by appropriate environmental intervention.

Genotype x environment interaction in the uptake of Cs and Sr from soils by plants

The soil-plant transfer factors for Cs and Sr were analyzed in relationship to soil properties, crops, and varieties of crops. Two crops and two varieties of each crop: lettuce (Lactuca sativa L.), cv. Salad Bowl Green and cv. Lobjoits Green Cos, and radish (Raphanus sativus L.), cv. French Breakfast 3 and cv. Scarlet Globe, were grown on five different soils amended with Cs and Sr to give concentrations of 1 mg kg(-1) and 50 mg kg(-1) of each element. Soil-plant transfer coefficients ranged between 0.12-19.10 (Cs) and 1.48-146.10 (Sr) for lettuce and 0.09-13.24 (Cs) and 2.99-93.00 (Sr) for radish. Uptake of Cs and Sr by plants depended on both plant and soil properties. There were significant (P less than or equal to 0.05) differences between soil-plant transfer factors for each plant type at the two soil concentrations. At each soil concentration about 60% of the variance in the uptake of the Cs and Sr was due to soil properties. For a given concentration of Cs or Sr in soil, the most important factor effecting soil-plant transfer of these elements was the soil properties rather than the crops or varieties of crops. Therefore, for the varieties considered here, soil-plant transfer of Cs and Sr would be best regulated through the management of soil properties. At each concentration of Cs and Sr, the main soil properties effecting the uptake of Cs and Sr by lettuce and radish were the concentrations of K and Ca, pH and CEC. Together with the concentrations of contaminants in soils, they explained about 80% of total data variance, and were the best predictors for soil-plant transfer. The different varieties of lettuce and radish gave different responses in soil-plant transfer of Cs and Sr in different soil conditions, i.e. genotype x environment interaction caused about 30% of the variability in the uptake of Cs and Sr by plants. This means that a plant variety with a low soil-plant transfer of Cs and Sr in one soil could have an increased soil-plant transfer factor in other soils. The broad implications of this work are that in contaminated agricultural lands still used for plant growing, contaminant-excluding crop varieties may not be a reliable method for decreasing contaminant transfer to foodstuffs. Modification of soil properties would be a more reliable technique. This is particularly relevant to agricultural soils in the former USSR still affected by fallout from the Chernobyl disaster.

Sequentially testing for a gene-drug interaction in a genomewide analysis

Assaying a large number of genetic markers from patients in clinical trials is now possible in order to tailor drugs with respect to efficacy. The statistical methodology for analysing such massive data sets is challenging. The most popular type of statistical analysis is to use a univariate test for each genetic marker, once all the data from a clinical study have been collected. This paper presents a sequential method for conducting an omnibus test for detecting gene-drug interactions across the genome, thus allowing informed decisions at the earliest opportunity and overcoming the multiple testing problems from conducting many univariate tests. We first propose an omnibus test for a fixed sample size. This test is based on combining F-statistics that test for an interaction between treatment and the individual single nucleotide polymorphism (SNP). As SNPs tend to be correlated, we use permutations to calculate a global p-value. We extend our omnibus test to the sequential case. In order to control the type I error rate, we propose a sequential method that uses permutations to obtain the stopping boundaries. The results of a simulation study show that the sequential permutation method is more powerful than alternative sequential methods that control the type I error rate, such as the inverse-normal method. The proposed method is flexible as we do not need to assume a mode of inheritance and can also adjust for confounding factors. An application to real clinical data illustrates that the method is computationally feasible for a large number of SNPs. Copyright (c) 2007 John Wiley & Sons, Ltd.

Effect of mountain breeze in ventilating the city under calm and neutral atmospheric environment: Interaction of airflow structures and ventilation efficiency

Many modern cities locate in the mountainous areas, like Hong Kong, Phoenix City and Los Angles. It is confirmed in the literature that the mountain wind system developed by differential heating or cooling can be very beneficial in ventilating the city nearby and alleviating the UHI effect. However, the direct interaction of mountain wind with the natural-convection circulation due to heated urban surfaces has not been studied, to our best knowledge. This kind of unique interaction of two kinds of airflow structures under calm and neutral atmospheric environment is investigated in this paper by CFD approach. A physical model comprising a simple mountain and three long building blocks (forming two street canyons) is firstly developed. Different airflow structures are identified within the conditions of different mountain-building height ratios (R=Hm/Hb) by varying building height but fixing mountain height. It is found that the higher ventilation rate in the street canyons is expected in the cases of smaller mountain-building ratios, indicating the stronger natural convection due to increasing heated building surfaces. However, there is the highest air change rate (ACH) in the lowest-building-height case and most of the air is advective into the street canyon through the top open area, highlighting the important role played by the mountain wind. In terms of the ventilation efficiency, it is shown that the smallest R case enjoys the best air change efficiency followed by the highest R case, while the worst ventilative street canyons occur at the middle R case. In the end, a gap across the streets is introduced in the modeling. The existence of the gap can greatly channel the mountain wind and distribute the air into streets nearby. Thus the ACH can be doubled and air quality can be significantly improved.

Genotype-environment interaction for post-weaning traits in Nellore beef cattle

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genotype by environment interaction in Nelore cattle from five Brazilian states

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of sex and age on genotype x environment interaction for beef cattle body weight studied using reaction norm models

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Prediction of Hevea progeny performance in the presence of genotype-environment interaction

Twenty two open-pollinated Hevea progenies from different parental clones of the Asian origin were tested at five sites in the Northwestern São Paulo State Brazil to investigate the progeny girth growth, rubber yield, bark thickness and plant height. Except for the rubber yield, the analysis of variance indicated highly significant (p<0.01) genotype x environment interaction and heterogeneity of regressions among the progenies. However, the regression stability analysis identified only a few interacting progenies which had regression coefficients significantly different from the expected value of one. The linear regressions of the progeny mean performance at each test on an environmental index (mean of all the progenies in each test) showed the general stability and adaptability of most selected Hevea progenies over the test environments. The few progenies which were responsive and high yielding on different test sites could be used to maximize the rubber cultivars productivity and to obtain the best use of the genetically improved stock under different environmental conditions.

Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Polymorphisms of DNA repair genes XRCC1 and XRCC3, interaction with environmental exposure and risk of chronic gastritis and gastric cancer

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genotype x environment interaction for age at first calving in Brazilian and Colombian Holsteins

The objective was to determine whether there is a genotype x environment interaction for age at first calving (AFC) in Holstein cattle in Brazil and Colombia. Data included 51,239 and 25,569 first-lactation records from Brazil and Colombia, respectively. Of 4230 sires in the data, 530 were North American sires used in both countries. Analyses were done using the REML bi-trait animal model, and AFC was considered as a distinct characteristic in each country. Fixed effects of contemporary group (herd-calving year), sire genetic group, and cow genetic group, and random effects of animal and residual variation were included in the model. Average AFC in Brazil and Colombia were 29.5 ± 4.0 and 32.1 ± 3.5 mo, respectively. Additive and residual genetic components and heritability coefficient for AFC in Brazil were 2.21 mo 2, 9.41 mo 2, and 0.19, respectively, whereas for Colombia, they were 1.02 mo 2, 6.84 mo 2, and 0.13, respectively. The genetic correlation of AFC between Brazil and Colombia was 0.78, indicating differences in ranking of sires consistent with a genotype x environment interaction. Therefore, in countries with differing environments, progeny of Holstein sires may calve at relatively younger or older ages compared with contemporary herdmates in one environment versus another.

Factors that cause genotype by environment interaction and use of a multiple-trait herd-cluster model for milk yield of Holstein cattle from Brazil and Colombia

Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.