Depression : genetic, epigenetic and DNA biobank studies

Depression is a disease that has an estimated lifetime prevalence of ~15% and a heritability of ~36%. There is support for a heterogeneous etiology of depression, which includes a) numerous genetic loci, b) various epigenetic contributors, and c) different environmental risk factors. The first five papers included in the present thesis investigate these three disease-contributing categories by studying a) the association of P11, NPY, MAOA and NR3C1, with depression, b) epigenetic marks like DNA methylation and histone modifications, and c) environmental influences, like childhood adversities, that may interact with certain genotypes and modulate the risk of depression. In two of these studies, there is also an attempt to pinpoint some targets and mechanisms of a current antidepressant drug and to examine the molecular effects of novel potential therapeutics. The thesis also includes a paper which investigates reasons behind public refusal to consent to participation in a human genetics repository; a so- called DNA biobank. Achieving high participation rates in DNA biobanks is a prerequisite for the identification of new genetic loci, already known to have small effect sizes, which are associated with complex disorders like depression. However, as addressed in this last paper, solidarity (i.e. the participation in research for the common good) seems to be at stake for DNA biobanks and is an issue that needs to be raised both by the scientific community and national policy-makers. Specifically, the data of this thesis 1) confirm a genetic association between NPY and depression, 2) show the existence of a MAOA x childhood-adversity interaction that increases the risk of depression, 3) demonstrate DNA methylation differences of P11 in depression-like states and of MAOA in depression, 4) verify the effect of childhood trauma on NR3C1 DNA methylation, 5) provide new insights into how Npy is transcriptionally regulated via an allele-specific epigenetic programming and describe an alternatively spliced Npy mRNA variant, 6) suggest that escitalopram (a selective serotonin reuptake inhibitor; SSRI) may exert part of its antidepressant function by affecting the expression of DNA methyltransferases (DNMTs) and DNA methylation levels, 7) support the antidepressant effect of running, and 8) provide awareness of the ethical problems posed by large-scale genomic studies that rely on DNA biobanking

Identification of signaling pathways related to drug efficacy in hepatocellular carcinoma via integration of phosphoproteomic, genomic and clinical data

Hepatocellular Carcinoma (HCC) is one of the leading causes of death worldwide, with only a handful of treatments effective in unresectable HCC. Most of the clinical trials for HCC using new generation interventions (drug-targeted therapies) have poor efficacy whereas just a few of them show some promising clinical outcomes [1]. This is amongst the first studies where the mode of action of some of the compounds extensively used in clinical trials is interrogated on the phosphoproteomic level, in an attempt to build predictive models for clinical efficacy. Signaling data are combined with previously published gene expression and clinical data within a consistent framework that identifies drug effects on the phosphoproteomic level and translates them to the gene expression level. The interrogated drugs are then correlated with genes differentially expressed in normal versus tumor tissue, and genes predictive of patient survival. Although the number of clinical trial results considered is small, our approach shows potential for discerning signaling activities that may help predict drug efficacy for HCC.National Institutes of Health (U.S.) (Grant U54-CA119267)National Institutes of Health (U.S.) (Grant R01-CA96504

Two dimensional Berezin-Li-Yau inequalities with a correction term

We improve the Berezin-Li-Yau inequality in dimension two by adding a positive correction term to its right-hand side. It is also shown that the asymptotical behaviour of the correction term is almost optimal. This improves a previous result by Melas.Comment: 6 figure

A cointegrating stock trading strategy: application to listed tanker shipping companies

In the current paper, we propose a strategy to trade a portfolio of listed shipping companies in the US market. In particular, we estimate a co-integrating relationship between the weekly stock market returns of a portfolio of tanker shipping companies and the Baltic Tanker Index, exploiting the close relationship between freight rates and the stock market performance of shipping companies. Our results suggest that a trading strategy on the basis of a co-integrating relationship and a simple moving average rule outperforms, by approximately 50%, a standard buy-and-hold strategy in various investment horizons, often by a very wide margin. Given the latter, the results allow us to enhance the current literature on shipping finance by providing evidence of how simple investment strategies can benefit both retail and institutional investors who do not have direct exposure or experience in the shipping industry by allowing them to include shipping stocks in their portfolios. The shipping industry has not been open for a wider circle of investors since its inception (Harlafti and Papakonstantinou 2013). Ties within the industry have been close and family relationships have been, most often than not, predominant (Harlaftis and Theotokas 2007). Nevertheless, the increase in vessel prices since the 1970s has brought up the question of whether shipping companies should use external lending financing or float in the markets. Nonetheless, it was not until the mid-2000s that an increasing number of shipping enterprises decided to relinquish information of their modus operandi and enlist in the world stock markets (Merikas et al. 2009). The increased number of companies in the market provided investors with an alternative way to invest in the shipping industry. Interested parties no longer need to acquire actual assets (vessels) but only hold stocks of shipping companies. Even in this case, however, little is currently known regarding the performance of the shipping companies in the stock market. The existing literature just provides information regarding IPOs (Merikas et al. 2009) and M&As (Alexandrou et al. 2014) in the industry. Nonetheless, there exists no study, at least to our knowledge, which employs a trading strategy based solely on shipping stock companies. In the current paper, we build on the literature’s premise that freight rates are the predominant factor which affects the companies’ performance (see also next Section) and propose a trading strategy for a portfolio of tanker shipping companies that are listed in the US stock markets. As expected, we find that these companies exhibit a long-run common path with the Baltic Tanker Index. Given this relationship, we propose a long-short trading strategy on the basis of a cointegration model and a simple moving average rule, which appears to outperform the classic buy-and-hold approach across various investment horizons, often by a wide margin. We have employed the buy-and-hold approach as a benchmark of our strategy, since it tends to be denoted to investors that are not actively trading in the stock markets (Shilling 1992). Thus, we propose that the specific active trading technique, that we propose, can give higher returns when compared to a passive investment strategy. The remainder of the paper is organized as follows: the next section provides a review of the existing literature on the shipping companies’ stock prices, their unique characteristics and the (non-stock market) trading strategies that have been introduced by other researchers. Section 3 presents the methodology and the data we have used, Section 4 offers the results and the last Section provides a general overview along with the conclusions reached by this paper

The impact of temperature changes on summer time ozone and its precursors in the Eastern Mediterranean

Changes in temperature due to variability in meteorology and climate change are expected to significantly impact atmospheric composition. The Mediterranean is a climate sensitive region and includes megacities like Istanbul and large urban agglomerations such as Athens. The effect of temperature changes on gaseous air pollutant levels and the atmospheric processes that are controlling them in the Eastern Mediterranean are here investigated. The WRF/CMAQ mesoscale modeling system is used, coupled with the MEGAN model for the processing of biogenic volatile organic compound emissions. A set of temperature perturbations (spanning from 1 to 5 K) is applied on a base case simulation corresponding to July 2004. The results indicate that the Eastern Mediterranean basin acts as a reservoir of pollutants and their precursor emissions from large urban agglomerations. During summer, chemistry is a major sink at these urban areas near the surface, and a minor contributor at downwind areas. On average, the atmospheric processes are more effective within the first 1000 m above ground. Temperature increases lead to increases in biogenic emissions by 9±3% K<sup>−1</sup>. Ozone mixing ratios increase almost linearly with the increases in ambient temperatures by 1±0.1 ppb O<sub>3</sub> K<sup>−1</sup> for all studied urban and receptor stations except for Istanbul, where a 0.4±0.1 ppb O<sub>3</sub> K<sup>−1</sup> increase is calculated, which is about half of the domain-averaged increase of 0.9±0.1 ppb O<sub>3</sub> K<sup>−1</sup>. The computed changes in atmospheric processes are also linearly related with temperature changes

Intracisternal delivery of NFκB-inducible scAAV2/9 reveals locoregional neuroinflammation induced by systemic kainic acid treatment.

We have previously demonstrated disease-dependent gene delivery in the brain using an AAV vector responding to NFκB activation as a probe for inflammatory responses. This vector, injected focally in the parenchyma prior to a systemic kainic acid (KA) injection mediated inducible transgene expression in the hippocampus but not in the cerebellum, regions, respectively, known to be affected or not by the pathology. However, such a focal approach relies on previous knowledge of the model parameters and does not allow to predict the whole brain response to the disease. Global brain gene delivery would allow to predict the regional distribution of the pathology as well as to deliver therapeutic factors in all affected brain regions. We show that self-complementary AAV2/9 (scAAV2/9) delivery in the adult rat cisterna magna allows a widespread but not homogenous transduction of the brain. Indeed, superficial regions, i.e., cortex, hippocampus, and cerebellum were more efficiently transduced than deeper regions, such as striatum, and substantia nigra. These data suggest that viral particles penetration from the cerebrospinal fluid (CSF) into the brain is a limiting factor. Interestingly, AAV2/9-2YF a rationally designed capsid mutant (affecting surface tyrosines) increased gene transfer efficiency approximately fivefold. Neurons, astrocytes, and oligodendrocytes, but not microglia, were transduced in varying proportions depending on the brain region and the type of capsid. Finally, after a single intracisternal injection of scAAV2/9-2YF using the NFκB-inducible promoter, KA treatment induced transgene expression in the hippocampus and cortex but not in the cerebellum, corresponding to the expression of the CD11b marker of microglial activation. These data support the use of disease-inducible vectors administered in the cisterna magna as a tool to characterize the brain pathology in systemic drug-induced or transgenic disease models. However, further improvements are required to enhance viral particles penetration into the brain

The Friction Coefficient of Fractal Aggregates in the Continuum and Transition Regimes

A methodology is introduced for friction-coefficient calculations of fractal-like aggregates that relates the friction coefficient to a solution of the diffusion equation. Synthetic fractal aggregates were created with a cluster-cluster aggregation algorithm. Their fiction coefficients were obtained from gas molecule-aggregate collision rates that were calculated with the COMSOL Multiphysics software. Results were compared and validated with literature values. The effect of aggregate structure on dynamical properties of the aggregate, in particular mobility, was also studied. Both the fractal dimension and the fractal prefactor are required to characterize fully an aggregate.JRC.F.8-Sustainable Transpor

New Constraints on Methane Fluxes and Rates of Anaerobic Methane Oxidation in a Gulf of Mexico Brine Pool via In Situ Mass Spectrometry

Deep-sea biogeochemical cycles are, in general, poorly understood owing to the difficulties of making measurements in situ, recovering samples with minimal perturbation, and, in many cases, coping with high spatial and temporal heterogeneity. In particular, biogeochemical fluxes of volatiles such as methane remain largely unconstrained because of the difficulties with accurate quantification in situ and the patchiness of point sources such as seeps and brine pools. To better constrain biogeochemical fluxes and cycling, we have developed a deep-sea in situ mass spectrometer (ISMS) to enable high-resolution quantification of volatiles in situ. Here we report direct measurements of methane concentrations made in a Gulf of Mexico brine pool located at a depth of over 2300 m. Concentrations of up to 33 mM methane were observed within the brine pool, whereas concentrations in the water directly above were three orders of magnitude lower. These direct measurements enabled us to make the first accurate estimates of the diffusive flux from a brine pool, calculated to be $1.1\pm0.2 mol m^{-2} yr^{-1}$. Integrated rate measurements of aerobic methane oxidation in the water column overlying the brine pool were $~320 \mu mol m^{-2} yr^{-1}$, accounting at most for just 0.03% of the diffusive methane flux from the brine pool. Calculated rates of anaerobic methane oxidation were $600-1200 \mu M yr^{-1}$, one to two orders of magnitude higher than previously published values of AOM in anoxic fluids. These findings suggest that brine pools are enormous point sources of methane in the deep sea, and may, in aggregate, have a pronounced impact on the global marine methane cycle.Organismic and Evolutionary Biolog

Investigating the quality of modeled aerosol profiles based on combined lidar and sunphotometer data

In this study we present an evaluation of the Comprehensive Air Quality Model with extensions (CAMx) for Thessaloniki using radiometric and lidar data. The aerosol mass concentration profiles of CAMx are compared against the PM2.5 and PM2. 5−10 concentration profiles retrieved by the Lidar-Radiometer Inversion Code (LIRIC). The CAMx model and the LIRIC algorithm results were compared in terms of mean mass concentration profiles, center of mass and integrated mass concentration in the boundary layer and the free troposphere. The mean mass concentration comparison resulted in profiles within the same order of magnitude and similar vertical structure for the PM2. 5 particles. The mean centers of mass values are also close, with a mean bias of 0.57 km. On the opposite side, there are larger differences for the PM2. 5−10 mode, both in the boundary layer and in the free troposphere. In order to grasp the reasons behind the discrepancies, we investigate the effect of aerosol sources that are not properly included in the model's emission inventory and in the boundary conditions such as the wildfires and the desert dust component. The identification of the cases that are affected by wildfires is performed using wind backward trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model in conjunction with satellite fire pixel data from MODerate-resolution Imaging Spectroradiometer (MODIS) Terra and Aqua global monthly fire location product MCD14ML. By removing those cases the correlation coefficient improves from 0.69 to 0.87 for the PM2. 5 integrated mass in the boundary layer and from 0.72 to 0.89 in the free troposphere. The PM2.5 center of mass fractional bias also decreases to 0.38 km. Concerning the analysis of the desert dust component, the simulations from the Dust Regional Atmospheric Model (BSC-DREAM8b) were deployed. When only the Saharan dust cases are taken into account, BSC-DREAM8b generally outperforms CAMx when compared with LIRIC, achieving a correlation of 0.91 and a mean bias of −29.1 % for the integrated mass in the free troposphere and a correlation of 0.57 for the center of mass. CAMx, on the other hand, underestimates the integrated mass in the free troposphere. Consequently, the accuracy of CAMx is limited concerning the transported Saharan dust cases. We conclude that the performance of CAMx appears to be best for the PM2.5 particles, both in the boundary layer and in the free troposphere. Sources of particles not properly taken into account by the model are confirmed to negatively affect its performance, especially for the PM2. 5−10 particles.The authors would like to acknowledge the EU projects MACC-III (Monitoring Atmospheric Composition and Climate – III, grant agreement no. 633080) and MACC-II project (Monitoring Atmospheric Composition and Climate – Interim Implementation, grant agreement no. 283576). The simulated results presented in this research paper have been produced using the EGI and HellasGrid infrastructures. The ACTRIS-2 project from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 654109 is gratefully acknowledged. The authors would also like to acknowledge the support provided by the Scientific Computing Center at Aristotle University of Thessaloniki throughout the progress of the work on air quality forecasting. BSC-DREAM8b simulations were performed on the Mare Nostrum supercomputer hosted by Barcelona Supercomputing Center-Centro Nacional de Supercomputacion (BSC-CNS). S. Basart wants to acknowledge the CICYT project (CGL2013-46736). Elina Giannakaki acknowledges the support of the Academy of Finland (project no. 270108).Peer ReviewedPostprint (published version