Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models

Twin studies have been adopted for decades to disentangle the relative genetic and environmental contributions for a wide range of traits. However, heritability estimation based on the classical twin models does not take into account dynamic behavior of the variance components over age. Varying variance of the genetic component over age can imply the existence of gene–environment (G × E) interactions that general genome-wide association studies (GWAS) fail to capture, which may lead to the inconsistency of heritability estimates between twin design and GWAS. Existing parametric G × E interaction models for twin studies are limited by assuming a linear or quadratic form of the variance curves with respect to a moderator that can, however, be overly restricted in reality. Here we propose spline-based approaches to explore the variance curves of the genetic and environmental components. We choose the additive genetic, common, and unique environmental variance components (ACE) model as the starting point. We treat the component variances as variance functions with respect to age modeled by B-splines or P-splines. We develop an empirical Bayes method to estimate the variance curves together with their confidence bands and provide an R package for public use. Our simulations demonstrate that the proposed methods accurately capture dynamic behavior of the component variances in terms of mean square errors with a data set of >10,000 twin pairs. Using the proposed methods as an alternative and major extension to the classical twin models, our analyses with a large-scale Finnish twin data set (19,510 MZ twins and 27,312 DZ same-sex twins) discover that the variances of the A, C, and E components for body mass index (BMI) change substantially across life span in different patterns and the heritability of BMI drops to ∼50% after middle age. The results further indicate that the decline of heritability is due to increasing unique environmental variance, which provides more insights into age-specific heritability of BMI and evidence of G × E interactions. These findings highlight the fundamental importance and implication of the proposed models in facilitating twin studies to investigate the heritability specific to age and other modifying factors.     

Stream diatom assemblages as predictors of climate

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Beta diversity of stream diatoms at two hierarchical spatial scales: implications for biomonitoring

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Does Future Diabetes Risk Impair Current Quality of Life? A Cross-Sectional Study of Health-Related Quality of Life in Relation to the Finnish Diabetes Risk Score (FINDRISC)

Objectives

Present study examines the relationship between the estimated risk of developing type 2 diabetes (T2D) and health-related quality of life (HRQoL). We quantify the association between Finnish Diabetes Risk Score (FINDRISC) and HRQoL, and examine the potential use of FINDRISC as tool to evaluate HRQoL indirectly.

Methods

We conducted a cross-sectional study comprising 707 Finnish people without a diagnosis of T2D between the ages of 51 and 75 years. The risk of developing T2D was assessed using the validated and widely used FINDRISC (range 0–26 points), and quality of life was measured using two preference-based HRQoL instruments (15D and SF-6D) and one health profile instrument (SF-36). Effects of the individual FINDRISC items and demographic and clinical characteristics, such as co-morbidities, on HRQoL were studied using multivariable Tobit regression models.

Results

Low HRQoL was significantly and directly associated with the estimated risk of developing T2D. An approximate 4–5 point change in FINDRISC score was observed to be associated with clinically noticeable changes in the preference-based instrument HRQoL index scores. The association between HRQoL and the risk of developing T2D was also observed for most dimensions of HRQoL in all applied HRQoL instruments. Overall, old age, lack of physical activity, obesity, and history of high blood glucose were the FINDRISC factors most prominently associated with lower HRQoL.

Conclusions

The findings may help the health care professionals to substantiate the possible improvement in glucose metabolism and HRQoL potentially achieved by lifestyle changes, and better convince people at high risk of T2D to take action towards healthier lifestyle habits. FINDRISC may also provide an accurate proxy for HRQoL, and thus by estimating the risk of T2D with the FINDRISC, information about patients’ HRQoL may also be obtained indirectly, when it is not feasible to use HRQoL instruments.     

Diatom Cooccurrence Shows Less Segregation than Predicted from Niche Modeling

Species cooccurrence patterns give significant insights into the processes shaping communities. While biotic interactions have been widely studied using cooccurrence analyses in animals and larger plants, studies about cooccurrences among micro-organisms are still relatively rare. We examined stream diatom cooccurrences in France through a national database of samples. In order to test the relative influence of environmental, biotic and spatial constraints on species’ incidence distribution, cooccurrence and nestedness patterns of real communities were compared with the patterns generated from a set of standard and environmentally constrained null models. Real communities showed a higher level of segregation than the most conservative standard null models, but a general aggregation of cooccurrences when compared to environmentally constrained null models. We did not find any evidence of limiting similarity between cooccurring species. Aggregations of species cooccurrences were associated with the high levels of nestedness. Altogether, these results suggested that biotic interactions were not structuring cooccurrences of diatom species at our study scale. Instead, the patterns were more likely to be related with colonization patterns, mass effect, and local temporal dynamics of diatom biofilms. We further highlight that the association of standard and environmentally constrained null models may give realistic insight into the cooccurrence patterns of microbial communities.     

Electroporation: Mechanism and transient expression, stable transformation and biological effects in plant protoplasts

The present state of knowledge about the mechanistic and theoretical aspects of electroporation is summarized. Parameters affecting the efficiency of transient expression and stable transformation of electroporated plant protoplasts are rewieved. Biological effects of electroporation on plant protoplasts are described.     

Densities of microtime rodents along a pollution gradient from a copper-nickel smelter

Population densities of microtine rodents were studied along an air pollution gradient in the Kola Peninsula, Russia, by long-term and short-term trapping. The study area is affected by high sulphur dioxide and heavy metal emissions from the Severonikel copper-nickel smelter in Monchegorsk. The density of Clethrionomys rufocanus, the most abundant vole species in the area, was lowest close to the smelter and increased with distance up to the farthest, less polluted trapping sites. Clethrionomys glareolus, C. rutilus and Lemmus lemmus were absent from the most severely damaged area and were also scarce at the moderately polluted area 28 km south of the smelter. Although the population of C. glareolus has previously been cyclic at the moderately polluted area, we were unable to demonstrate any regular cycle. The most likely explanation for the low number of microtine rodents in the damaged and moderately polluted areas in a decrease in the quantity of important food plants: epiphytic lichens for C. glareolus and possibly C. rutilus, mosses for L. lemmus and seed plants, especially Vaccinium myrtillus, for C. rufocanus. Close to the smelter, direct toxic effects of heavy metals may also reduce population densities. The results show that pollutants may change the relative proportions of microtine species.     

Up-regulation, modification, and translocation of S100A6 induced by exposure to ionizing radiation revealed by proteomics profiling

The cellular response to genotoxic stress is a complex cascade of events including altered protein expression, interactions, modifications, and relocalization, leading to cell cycle arrest and DNA repair or to apoptosis. p53 protein has a central role in this process, and p53 status is an important factor in the response of a tumor to genotoxic anticancer therapy. We studied p53-related changes postexposure to ionizing radiation using top-down mass spectrometry. Initially two cell lines were compared, HCT116 p53 wild type (wt) and p53(-/-), in a time course study postirradiation. In the p53 wt cell line a striking increase of a 10.2-kDa protein was detected, and this protein was identified with MS/MS analysis as S100A6. Further MS profiling led to detection of two post-translationally modified variants of S100A6, namely glutathionylated and cysteinylated forms. In p53 wt cells, a specific shift from glutathionylated to cysteinylated S100A6 occurred postirradiation. The p53 dependence of this specific change in protein level and modification pattern of S100A6 postirradiation was confirmed in a panel of four lung cancer cell lines (H23, U1810, H69, and A549) with different p53 status and using small interfering RNA against p53. Interestingly the closely related S100 family protein S100A4 showed the same changes in modification pattern post-ionizing radiation in the p53 wt lung cancer cell line, and S100A4 also showed p53-dependent expression. Using confocal microscopy, relocalization of S100A6 from nucleus to cytosol and a colocalization with tropomyosin in stress fibers was detected in A549 cells postirradiation. This relocalization coincided with the change in S100A6 modification pattern. Based on these results, we suggest that S100A6 and S100A4 are regulated via redox modifications in vivo and that these proteins are involved in the cellular response to genotoxic stress.