Comparison of Population-Based Association Study Methods Correcting for Population Stratification

Population stratification can cause spurious associations in population–based association studies. Several statistical methods have been proposed to reduce the impact of population stratification on population–based association studies. We simulated a set of stratified populations based on the real haplotype data from the HapMap ENCODE project, and compared the relative power, type I error rates, accuracy and positive prediction value of four prevailing population–based association study methods: traditional case-control tests, structured association (SA), genomic control (GC) and principal components analysis (PCA) under various population stratification levels. Additionally, we evaluated the effects of sample sizes and frequencies of disease susceptible allele on the performance of the four analytical methods in the presence of population stratification. We found that the performance of PCA was very stable under various scenarios. Our comparison results suggest that SA and PCA have comparable performance, if sufficient ancestral informative markers are used in SA analysis. GC appeared to be strongly conservative in significantly stratified populations. It may be better to apply GC in the stratified populations with low stratification level. Our study intends to provide a practical guideline for researchers to select proper study methods and make appropriate inference of the results in population-based association studies

Neural networks for modeling gene-gene interactions in association studies

<p>Abstract</p> <p>Background</p> <p>Our aim is to investigate the ability of neural networks to model different two-locus disease models. We conduct a simulation study to compare neural networks with two standard methods, namely logistic regression models and multifactor dimensionality reduction. One hundred data sets are generated for each of six two-locus disease models, which are considered in a low and in a high risk scenario. Two models represent independence, one is a multiplicative model, and three models are epistatic. For each data set, six neural networks (with up to five hidden neurons) and five logistic regression models (the null model, three main effect models, and the full model) with two different codings for the genotype information are fitted. Additionally, the multifactor dimensionality reduction approach is applied.</p> <p>Results</p> <p>The results show that neural networks are more successful in modeling the structure of the underlying disease model than logistic regression models in most of the investigated situations. In our simulation study, neither logistic regression nor multifactor dimensionality reduction are able to correctly identify biological interaction.</p> <p>Conclusions</p> <p>Neural networks are a promising tool to handle complex data situations. However, further research is necessary concerning the interpretation of their parameters.</p

Intrinsic Capability of Budding Yeast Cofilin to Promote Turnover of Tropomyosin-Bound Actin Filaments

The ability of actin filaments to function in cell morphogenesis and motility is closely coupled to their dynamic properties. Yeast cells contain two prominent actin structures, cables and patches, both of which are rapidly assembled and disassembled. Although genetic studies have shown that rapid actin turnover in patches and cables depends on cofilin, how cofilin might control cable disassembly remains unclear, because tropomyosin, a component of actin cables, is thought to protect actin filaments against the depolymerizing activity of ADF/cofilin. We have identified cofilin as a yeast tropomyosin (Tpm1) binding protein through Tpm1 affinity column and mass spectrometry. Using a variety of assays, we show that yeast cofilin can efficiently depolymerize and sever yeast actin filaments decorated with either Tpm1 or mouse tropomyosins TM1 and TM4. Our results suggest that yeast cofilin has the intrinsic ability to promote actin cable turnover, and that the severing activity may rely on its ability to bind Tpm1

Growth of nanostructures by cluster deposition : a review

This paper presents a comprehensive analysis of simple models useful to analyze the growth of nanostructures obtained by cluster deposition. After detailing the potential interest of nanostructures, I extensively study the first stages of growth (the submonolayer regime) by kinetic Monte-Carlo simulations. These simulations are performed in a wide variety of experimental situations : complete condensation, growth with reevaporation, nucleation on defects, total or null cluster-cluster coalescence... The main scope of the paper is to help experimentalists analyzing their data to deduce which of those processes are important and to quantify them. A software including all these simulation programs is available at no cost on request to the author. I carefully discuss experiments of growth from cluster beams and show how the mobility of the clusters on the surface can be measured : surprisingly high values are found. An important issue for future technological applications of cluster deposition is the relation between the size of the incident clusters and the size of the islands obtained on the substrate. An approximate formula which gives the ratio of the two sizes as a function of the melting temperature of the material deposited is given. Finally, I study the atomic mechanisms which can explain the diffusion of the clusters on a substrate and the result of their mutual interaction (simple juxtaposition, partial or total coalescence...)Comment: To be published Rev Mod Phys, Oct 99, RevTeX, 37 figure

Divalent cation-, nucleotide-, and polymerization-dependent changes in the conformation of subdomain 2 of actin.

Conformational changes in subdomain 2 of actin were investigated using fluorescence probes dansyl cadaverine (DC) or dansyl ethylenediamine (DED) covalently attached to Gln41. Examination of changes in the fluorescence emission spectra as a function of time during Ca2+/Mg2+ and ATP/ADP exchange at the high-affinity site for divalent cation-nucleotide complex in G-actin confirmed a profound influence of the type of nucleotide but failed to detect a significant cation-dependent difference in the environment of Gln41. No significant difference between Ca- and Mg-actin was also seen in the magnitude of the fluorescence changes resulting from the polymerization of these two actin forms. Evidence is presented that earlier reported cation-dependent differences in the conformation of the loop 38-52 may be related to time-dependent changes in the conformation of subdomain 2 in DED- or DC-labeled G-actin, accelerated by substitution of Mg2+ for Ca2+ in CaATP-G-actin and, in particular, by conversion of MgATP- into MgADP-G-actin. These spontaneous changes are associated with a denaturation-driven release of the bound nucleotide that is promoted by two effects of DED or DC labeling: lowered affinity of actin for nucleotide and acceleration of ATP hydrolysis on MgATP-G-actin that converts it into a less stable MgADP form. Evidence is presented that the changes in the environment of Gln41 accompanying actin polymerization result in part from the release of Pi after the hydrolysis of ATP on the polymer. A similarity of this change to that accompanying replacement of the bound ATP with ADP in G-actin is discussed

Irreversible modification of magnetic properties of Pt/Co/Pt ultrathin films by femtosecond laser pulses

Contains fulltext : 127870.pdf (publisher's version ) (Open Access

Are sleep duration, midpoint of sleep and sleep quality associated with dietary intake among Bavarian adults?

BACKGROUND/OBJECTIVES: Only few epidemiologic studies examined sleep characteristics in relation to dietary behaviour. Our aim was to analyse associations of sleep duration, midpoint of sleep and sleep quality with dietary intake among the Bavarian population. SUBJECTS/METHODS: Within the cross-sectional Bavarian Food Consumption Survey II, 1050 subjects aged 13-81 years were recruited. Dietary intake was assessed with three 24-h dietary recalls by telephone (EPIC-Soft). In our study, 814 participants aged 18 years or older, who completed at least two 24-h dietary recalls and who had complete and plausible information on sleep characteristics were analysed. Dietary intake was described by the consumption of main food groups, energy-proving nutrients and energy intake. Sleep was measured by the Pittsburgh Sleep Quality Index Questionnaire, from which categories of self-reported usual sleep duration in half-h-steps per night, midpoint of sleep and overall sleep quality were derived. RESULTS: Sleep duration was associated with intake of non-alcoholic beverages (P&lt;0.01), carbonated beverages (P=0.04), water (P=0.04) and coffee/black tea (P=0.01) with higher intake among short duration sleepers. No association was found between the consumption of other main food groups, energy-proving nutrients or total daily energy intake and sleep duration. Midpoint of sleep was associated with intake of carbonated beverages (P=0.02, highest intake among subjects with early midpoint of sleep). No association between sleep quality and dietary intake was detected. CONCLUSIONS: Our findings demonstrate only specific associations between sleep characteristics and dietary intake, and mainly sleep duration was associated with beverage intake

Differential associations between diet and prediabetes or diabetes in the KORA FF4 study.

Type 2 diabetes mellitus (T2DM) is a global public health epidemic. Diet and lifestyle changes have been demonstrated as effective measures in managing T2DM and preventing or delaying the progression from prediabetes to diabetes, yet the relationship between diet, prediabetes and diabetes is still not entirely clear. The present study aimed to further elucidate the relationship between diet, diabetes and especially prediabetes. A total of 1542 participants of the cross-sectional, population-based Cooperative Health Research in the Region of Augsburg (KORA) FF4 study (2013/2014) were included in this analysis. Dietary intake was derived using a method combining information from a FFQ and repeated 24-h food lists. Glucose tolerance status was assessed via oral glucose tolerance tests in all participants without a previous physician-confirmed diagnosis of T2DM, and was classified according to the 2003 American Diabetes Association criteria. Crude and fully adjusted multinomial logistic regression models were fitted to examine associations between diet and prediabetes, undetected diabetes mellitus (UDM) and prevalent T2DM. After adjusting for major covariates, fruit was significantly inversely and total meat, processed meat, sugar-sweetened beverages and moderate alcohol significantly associated with UDM and/or prevalent diabetes. Sex-specific analyses showed that in men, coffee was significantly inversely (OR 0&middot;80; 95&nbsp;% CI 0&middot;67, 0&middot;96) and heavy alcohol significantly (OR 1&middot;84; 95&nbsp;% CI 1&middot;14, 2&middot;95) associated with prediabetes. Our findings on diet and T2DM are consistent with current literature, while our results regarding coffee, heavy alcohol consumption and prediabetes highlight new possible targets for primary prevention of the derangement of glucose homeostasis