Common variants at 12q14 and 12q24 are associated with hippocampal volume

Aging is associated with reductions in hippocampal volume that are accelerated by Alzheimer's disease and vascular risk factors. Our genome-wide association study (GWAS) of dementia-free persons (n = 9,232) identified 46 SNPs at four loci with P values of <4.0 × 10(-7). In two additional samples (n = 2,318), associations were replicated at 12q14 within MSRB3-WIF1 (discovery and replication; rs17178006; P = 5.3 × 10(-11)) and at 12q24 near HRK-FBXW8 (rs7294919; P = 2.9 × 10(-11)). Remaining associations included one SNP at 2q24 within DPP4 (rs6741949; P = 2.9 × 10(-7)) and nine SNPs at 9p33 within ASTN2 (rs7852872; P = 1.0 × 10(-7)); along with the chromosome 12 associations, these loci were also associated with hippocampal volume (P < 0.05) in a third younger, more heterogeneous sample (n = 7,794). The SNP in ASTN2 also showed suggestive association with decline in cognition in a largely independent sample (n = 1,563). These associations implicate genes related to apoptosis (HRK), development (WIF1), oxidative stress (MSR3B), ubiquitination (FBXW8) and neuronal migration (ASTN2), as well as enzymes targeted by new diabetes medications (DPP4), indicating new genetic influences on hippocampal size and possibly the risk of cognitive decline and dementia.     

Adaptive Evolutionary Neural Networks for Forecasting and Trading without a Data‐Snooping Bias

In this paper, we present two neural‐network‐based techniques: an adaptive evolutionary multilayer perceptron (aDEMLP) and an adaptive evolutionary wavelet neural network (aDEWNN). The two models are applied to the task of forecasting and trading the SPDR Dow Jones Industrial Average (DIA), the iShares NYSE Composite Index Fund (NYC) and the SPDR S&P 500 (SPY) exchange‐traded funds (ETFs). We benchmark their performance against two traditional MLP and WNN architectures, a smooth transition autoregressive model (STAR), a moving average convergence/divergence model (MACD) and a random walk model. We show that the proposed architectures present superior forecasting and trading performance compared to the benchmarks and are free from the limitations of the traditional neural networks such as the data‐snooping bias and the time‐consuming and biased processes involved in optimizing their parameters. Copyright © 2015 John Wiley & Sons, Ltd.     

The influence of habitat features on amphibian distribution in Northeastern Greece

Environmental and isolation variables relating to abundance of breeding amphibians, species richness and community structure at different spatial scales were examined in the Dadia-Lefkimi-Soufli Forest National Park, Evros, Greece. Logistic regression and a generalized linear model were used to relate several habitat characteristics to species occurrence and species richness. The community structure responses to breeding-pond features were examined at four spatial scales using canonical correspondence analysis (CCA). The richest communities live in low-altitude ponds, with stony or clay bottoms, high solar exposure and abundant submerged and floating vegetation. The CCA models were significant (p < 0.005) and revealed the influence of altitude, percentage of field and broadleaf forest coverage, and number of water bodies on amphibian species assemblages at all four spatial scales. There is a specific need for holistic management of amphibians that will consider habitat connectivity, particularly between aquatic and terrestrial habitats, at a larger, more interconnected scale.     

From in vivo to in silico biology and back

The massive acquisition of data in molecular and cellular biology has led to the renaissance of an old topic: simulations of biological systems. Simulations, increasingly paired with experiments, are being successfully and routinely used by computational biologists to understand and predict the quantitative behaviour of complex systems, and to drive new experiments. Nevertheless, many experimentalists still consider simulations an esoteric discipline only for initiates. Suspicion towards simulations should dissipate as the limitations and advantages of their application are better appreciated, opening the door to their permanent adoption in everyday research.     

Current issues in mouse genome engineering

The mouse is the foremost vertebrate experimental model because its genome can be precisely and variously engineered. Now that the mouse genome has been sequenced and annotated, the task of mutating each gene is feasible, and an international cooperation is providing mutated embryonic stem cells and mice as readily available resources. Because these resources will change biomedical research, decisions about their nature will have far-reaching effects. It is therefore timely to consider topical issues for mouse genome engineering, such as the background genotype; homologous, site-specific and transpositional recombination; conditional mutagenesis; RNA-mediated interference; and functional genomics with embryonic stem cells.     

Variants conferring risk of atrial fibrillation on chromosome 4q25

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in humans and is characterized by chaotic electrical activity of the atria. It affects one in ten individuals over the age of 80 years, causes significant morbidity and is an independent predictor of mortality. Recent studies have provided evidence of a genetic contribution to AF. Mutations in potassium-channel genes have been associated with familial AF but account for only a small fraction of all cases of AF. We have performed a genome-wide association scan, followed by replication studies in three populations of European descent and a Chinese population from Hong Kong and find a strong association between two sequence variants on chromosome 4q25 and AF. Here we show that about 35% of individuals of European descent have at least one of the variants and that the risk of AF increases by 1.72 and 1.39 per copy. The association with the stronger variant is replicated in the Chinese population, where it is carried by 75% of individuals and the risk of AF is increased by 1.42 per copy. A stronger association was observed in individuals with typical atrial flutter. Both variants are adjacent to PITX2, which is known to have a critical function in left-right asymmetry of the heart.     

Modelling and Trading the English and German Stock Markets with Novelty Optimization Techniques

The motivation for this paper was the introduction of novel short‐term models to trade the FTSE 100 and DAX 30 exchange‐traded funds (ETF) indices. There are major contributions in this paper which include the introduction of an input selection criterion when utilizing an expansive universe of inputs, a hybrid combination of partial swarm optimizer (PSO) with radial basis function (RBF) neural networks, the application of a PSO algorithm to a traditional autoregressive moving model (ARMA), the application of a PSO algorithm to a higher‐order neural network and, finally, the introduction of a multi‐objective algorithm to optimize statistical and trading performance when trading an index. All the machine learning‐based methodologies and the conventional models are adapted and optimized to model the index. A PSO algorithm is used to optimize the weights in a traditional RBF neural network, in a higher‐order neural network (HONN) and the AR and MA terms of an ARMA model. In terms of checking the statistical and empirical accuracy of the novel models, we benchmark them with a traditional HONN, with an ARMA, with a moving average convergence/divergence model (MACD) and with a naïve strategy. More specifically, the trading and statistical performance of all models is investigated in a forecast simulation of the FTSE 100 and DAX 30 ETF time series over the period January 2004 to December 2015 using the last 3 years for out‐of‐sample testing. Finally, the empirical and statistical results indicate that the PSO‐RBF model outperforms all other examined models in terms of trading accuracy and profitability, even with mixed inputs and with only autoregressive inputs. Copyright © 2016 John Wiley & Sons, Ltd.