Subclinical hypothyroidism and the risk of coronary heart disease: a meta-analysis.

PURPOSE: Subclinical hypothyroidism has been associated with elevated cholesterol and increased risk for atherosclerosis, but data on the risk of coronary heart disease (CHD) are conflicting. We performed a systematic review to determine whether subclinical hypothyroidism is associated with CHD in adults. METHODS: We searched MEDLINE from 1966 to April 2005, and the bibliographies of key articles to identify studies that provided risk estimates for CHD or cardiovascular mortality associated with subclinical hypothyroidism. Two authors independently reviewed each potential study for eligibility, assessed methodologic quality, and extracted the data. RESULTS: We identified 14 observational studies that met eligibility criteria. Subclinical hypothyroidism increased the risk of CHD (summary odds ratio [OR]: 1.65, 95% confidence interval [CI], 1.28-2.12). The summary OR for CHD was 1.81 (CI, 1.38-2.39) in 9 studies adjusted or matched for demographic characteristics, and 2.38 (CI, 1.53-3.69) after pooling the studies that adjusted for most cardiovascular risk factors. Sensitivity analyses including only population-based studies and those with formal outcome adjudication procedures yielded similar results. Subgroup analyses by type of study design showed a similar trend, but lower risk, in the 5 prospective cohort studies (OR 1.42, CI, 0.91-2.21), compared with the case-control and cross-sectional studies (OR 1.72, CI, 1.25-2.38). CONCLUSION: Our systematic review indicates that subclinical hypothyroidism is associated with an increased risk of CHD. Clinical trials are needed to assess whether thyroxine replacement reduces the risk of CHD in subjects with subclinical hypothyroidism.

Measuring Party Positions and Issue Salience from Media Coverage: Introducing and Cross-Validating New Indicators

Recent studies have started to use media data to measure party positions and issue salience. The aim of this article is to compare and cross-validate this alternative approach with the more commonly used party manifestos, expert judgments and mass surveys. To this purpose, we present two methods to generate indicators of party positions and issue salience from media coverage: the core sentence approach and political claims analysis. Our cross-validation shows that with regard to party positions, indicators derived from the media converge with traditionally used measurements from party manifestos, mass surveys and expert judgments, but that salience indicators measure different underlying constructs. We conclude with a discussion of specific research questions for which media data offer potential advantages over more established methods.

Use of LIDAR-based Elevation Data for Highway Drainage Analysis: A Qualitative Assessment, 2003

US Geological Survey (USGS) based elevation data are the most commonly used data source for highway hydraulic analysis; however, due to the vertical accuracy of USGS-based elevation data, USGS data may be too “coarse” to adequately describe surface profiles of watershed areas or drainage patterns. Additionally hydraulic design requires delineation of much smaller drainage areas (watersheds) than other hydrologic applications, such as environmental, ecological, and water resource management. This research study investigated whether higher resolution LIDAR based surface models would provide better delineation of watersheds and drainage patterns as compared to surface models created from standard USGS-based elevation data. Differences in runoff values were the metric used to compare the data sets. The two data sets were compared for a pilot study area along the Iowa 1 corridor between Iowa City and Mount Vernon. Given the limited breadth of the analysis corridor, areas of particular emphasis were the location of drainage area boundaries and flow patterns parallel to and intersecting the road cross section. Traditional highway hydrology does not appear to be significantly impacted, or benefited, by the increased terrain detail that LIDAR provided for the study area. In fact, hydrologic outputs, such as streams and watersheds, may be too sensitive to the increased horizontal resolution and/or errors in the data set. However, a true comparison of LIDAR and USGS-based data sets of equal size and encompassing entire drainage areas could not be performed in this study. Differences may also result in areas with much steeper slopes or significant changes in terrain. LIDAR may provide possibly valuable detail in areas of modified terrain, such as roads. Better representations of channel and terrain detail in the vicinity of the roadway may be useful in modeling problem drainage areas and evaluating structural surety during and after significant storm events. Furthermore, LIDAR may be used to verify the intended/expected drainage patterns at newly constructed highways. LIDAR will likely provide the greatest benefit for highway projects in flood plains and areas with relatively flat terrain where slight changes in terrain may have a significant impact on drainage patterns.

Exploratory Factor Analysis of the contents and styles of irrational thoughts assessed by "The Attitudes and Beliefs Inventory"

The factor structure of a back translated Spanish version (Lega, Caballo and Ellis, 2002) of the Attitudes and Beliefs Inventory (ABI) (Burgess, 1990) is analyzed in a sample of 250 university students.The Spanish version of the ABI is a 48-items self-report inventory using a 5-point Likert scale that assesses rational and irrational attitudes and beliefs. 24-items cover two dimensions of irrationality: a) areas of content (3 subscales), and b) styles of thinking (4 subscales).An Exploratory Factor Analysis (Parallel Analysis with Unweighted Least Squares method and Promin rotation) was performed with the FACTOR 9.20 software (Lorenzo-Seva and Ferrando, 2013).The results reproduced the main four styles of irrational thinking in relation with the three specific contents of irrational beliefs. However, two factors showed a complex configuration with important cross-loadings of different items in content and style. More analyses are needed to review the specific content and style of such items.

An integrative computational analysis provides evidence for FBN1-associated network deregulation in trisomy 21

Although approximately 50% of Down Syndrome (DS) patients have heart abnormalities, they exhibit an overprotection against cardiac abnormalities related with the connective tissue, for example a lower risk of coronary artery disease. A recent study reported a case of a person affected by DS who carried mutations in FBN1, the gene causative for a connective tissue disorder called Marfan Syndrome (MFS). The fact that the person did not have any cardiac alterations suggested compensation effects due to DS. This observation is supported by a previous DS meta-analysis at the molecular level where we have found an overall upregulation of FBN1 (which is usually downregulated in MFS). Additionally, that result was cross-validated with independent expression data from DS heart tissue. The aim of this work is to elucidate the role of FBN1 in DS and to establish a molecular link to MFS and MFS-related syndromes using a computational approach. To reach that, we conducted different analytical approaches over two DS studies (our previous meta-analysis and independent expression data from DS heart tissue) and revealed expression alterations in the FBN1 interaction network, in FBN1 co-expressed genes and FBN1-related pathways. After merging the significant results from different datasets with a Bayesian approach, we prioritized 85 genes that were able to distinguish control from DS cases. We further found evidence for several of these genes (47%), such as FBN1, DCN, and COL1A2, being dysregulated in MFS and MFS-related diseases. Consequently, we further encourage the scientific community to take into account FBN1 and its related network for the study of DS cardiovascular characteristics.

Gazpacho consumption is associated with lower blood pressure and reduced hypertension in a high cardiovascular risk cohort. Cross-sectional study of the PREDIMED trial

Hypertension is a major public health problem and a leading cause of death and disability in both developed and developing countries, affecting onequarter of the world"s adult population. Our aim was to evaluate whether the consumption of gazpacho, a Mediterranean vegetable-based cold soup rich in phytochemicals, is associated with lower blood pressure (BP) and/or reduced prevalence of hypertension in individuals at high cardiovascular risk. Methods and results: We selected 3995 individuals (58% women, mean age 67 y) at high cardiovascular risk (81% hypertensive) recruited into the PREDIMED study. BP, weight, and dietary and physical activity data were collected. In multivariate linear regression analyses, after adjustment, moderate and high gazpacho consumption categories were associated with reduced mean systolic BP of 1.9 mm Hg [95% confidence interval (CI): 3.4; 0.6] and 2.6 mm Hg (CI: 4.2; 1.0), respectively, and reduced diastolic BP of 1.5 mm Hg (CI: 2.3; 0.6) and 1.9 mm Hg (CI: 2.8; 1.1). By multiple-adjusted logistic regression analysis, gazpacho consumption was associated with a lower prevalence of hypertension, with OR Z 0.85 (CI: 0.73; 0.99) for each 250 g/week increase and OR Z 0.73 (CI: 0.55; 0.98) for high gazpacho consumption groups compared to the no-consumption group. Conclusions: Gazpacho consumption was inversely associated with systolic and diastolic BP and prevalence of hypertension in a cross-sectional Mediterranean population at high cardiovascular risk. The association between gazpacho intake and reduction of BP is probably due to synergy among several bioactive compounds present in the vegetable ingredients used to make the recipe.

Gazpacho consumption is associated with lower blood pressure and reduced hypertension in a high cardiovascular risk cohort. Cross-sectional study of the PREDIMED trial

Hypertension is a major public health problem and a leading cause of death and disability in both developed and developing countries, affecting onequarter of the world"s adult population. Our aim was to evaluate whether the consumption of gazpacho, a Mediterranean vegetable-based cold soup rich in phytochemicals, is associated with lower blood pressure (BP) and/or reduced prevalence of hypertension in individuals at high cardiovascular risk. Methods and results: We selected 3995 individuals (58% women, mean age 67 y) at high cardiovascular risk (81% hypertensive) recruited into the PREDIMED study. BP, weight, and dietary and physical activity data were collected. In multivariate linear regression analyses, after adjustment, moderate and high gazpacho consumption categories were associated with reduced mean systolic BP of 1.9 mm Hg [95% confidence interval (CI): 3.4; 0.6] and 2.6 mm Hg (CI: 4.2; 1.0), respectively, and reduced diastolic BP of 1.5 mm Hg (CI: 2.3; 0.6) and 1.9 mm Hg (CI: 2.8; 1.1). By multiple-adjusted logistic regression analysis, gazpacho consumption was associated with a lower prevalence of hypertension, with OR Z 0.85 (CI: 0.73; 0.99) for each 250 g/week increase and OR Z 0.73 (CI: 0.55; 0.98) for high gazpacho consumption groups compared to the no-consumption group. Conclusions: Gazpacho consumption was inversely associated with systolic and diastolic BP and prevalence of hypertension in a cross-sectional Mediterranean population at high cardiovascular risk. The association between gazpacho intake and reduction of BP is probably due to synergy among several bioactive compounds present in the vegetable ingredients used to make the recipe.

Driving under drugs in Switzerland : a descriptive cross-sectional study

Objectives: Many drugs, both illicit or for medication, are known to influence driving abilities and increase risks of accidents. We explored the prevalence of psychoactive substances in a random sample of drivers in Switzerland. Methods: Saliva samples from 1078 random drivers were collected at 24 different locations in Western Switzerland from October 2006 to April 2008 for complete toxicological analysis using liquid chromatography/tandem mass spectrometry. Results: Provisional results are available for 437 drivers. 6.2% (CI95% 4.1 to 8.9) were under the influence of illicit drugs and 8.7% under psychoactive medication (CI95% 6.2 to 11.7). 37 drivers (8.5%) were under the influence of alcohol of which 14 (3.2%) were above 0.8 mg/L. 21 drivers (4.8%) were under the combined influence of more than one psychoactive substance; however only 4 drivers (0.9%) were under both the influence of medication and alcohol. Looking more specifically at illicit substances, 22 (5.0%) were positive to cocaine, 5 (1.1%) to cannabis, and 2 (0.5%) to amphetamines ; for psychoactive medication, 17 (3.9%) were positive to benzodiazepines, 16 (3.7%) to antidepressors, 7 (1.6%) to opiates, 7 (1.6%) to neuroleptics, and 3 (0.7%) to other substances influencing driving abilities. 17/21 drivers did not self-report their consumption of drugs whereas only 9/35 failed mentioning their medication. Men drivers were 3.2 times (CI95% 1.1 to 9.5) more likely to be under the influence of illicit drugs than women. Full results will be reported when laboratory data will be available in April. Conclusions: Driving under the influence of psychoactive substances is common. In Western Switzerland, prevention messages could focus on men, driving under medication or cocaine.

La perception subjective de l'effet des neuroleptiques chez des patients schizophrènes ambulatoires: une étude transversale [Subjective perception of the effect of neuroleptics by outpatient schizophrenic patients: a cross-sectional study].

Subjective response to neuroleptics is essential to long term observance of treatment and quality of life of patients. Numerous factors (pharmacological, relational and psychopathological) are responsible of this subjective response. Objectives of this study are: (a) to examine psychometric features of the french version of the Drug Attitude Inventory (DAI-30) [13] and (b) to explore pharmacological, relational and psychopathological factors related to this subjective response. Subjects and methods: 78 subjects were rated (self rated response rate 61% (n = 48)) for (a) subjective response to neuroleptics, (b) compliance, (c) therapeutic alliance, (d) symptoms (e) severity of disorder. RESULTS: Factor analysis yielded 2 main clinically relevant factors, similar to the original version: (I) global subjective response and (II) specific subjective response. Internal consistency is high. Correspondance analysis showed two important dimensions in the treatment of schizophrenic patients: (I) Recovery--aggravation, (II) Therapeutic ambition--positive or negative symptoms. CONCLUSION: French version of DAI-30 seems to have a similar structure and psychometric features as the original version. It shows concordance with the degree of compliance. Pharmacological factors are not the only factors implicated in subjective response, but are still to be identified. Limitations of our study are: (a) nonhomogenous indication for treatment, (b) small rate and degree of non compliance in our sample. Relationships between therapeutic ambition, type of symptoms and treatment outcome should be further studied.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Exploratory Factor Analysis of the contents and styles of irrational thoughts assessed by "The Attitudes and Beliefs Inventory"

The factor structure of a back translated Spanish version (Lega, Caballo and Ellis, 2002) of the Attitudes and Beliefs Inventory (ABI) (Burgess, 1990) is analyzed in a sample of 250 university students.The Spanish version of the ABI is a 48-items self-report inventory using a 5-point Likert scale that assesses rational and irrational attitudes and beliefs. 24-items cover two dimensions of irrationality: a) areas of content (3 subscales), and b) styles of thinking (4 subscales).An Exploratory Factor Analysis (Parallel Analysis with Unweighted Least Squares method and Promin rotation) was performed with the FACTOR 9.20 software (Lorenzo-Seva and Ferrando, 2013).The results reproduced the main four styles of irrational thinking in relation with the three specific contents of irrational beliefs. However, two factors showed a complex configuration with important cross-loadings of different items in content and style. More analyses are needed to review the specific content and style of such items.

Bayesian Markov-chain-Monte-Carlo inversion of time-lapse cross hole ground-penetrating radar data to characterize the vadose zone at the Arrenaes field site, Denmark

The ground-penetrating radar (GPR) geophysical method has the potential to provide valuable information on the hydraulic properties of the vadose zone because of its strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR traveltime data can allow for a significant reduction in uncertainty regarding subsurface van Genuchten-Mualem (VGM) parameters. Much of the previous work on the stochastic estimation of VGM parameters from crosshole GPR data has considered the case of steady-state infiltration conditions, which represent only a small fraction of practically relevant scenarios. We explored in detail the dynamic infiltration case, specifically examining to what extent time-lapse crosshole GPR traveltimes, measured during a forced infiltration experiment at the Arreneas field site in Denmark, could help to quantify VGM parameters and their uncertainties in a layered medium, as well as the corresponding soil hydraulic properties. We used a Bayesian Markov-chain-Monte-Carlo inversion approach. We first explored the advantages and limitations of this approach with regard to a realistic synthetic example before applying it to field measurements. In our analysis, we also considered different degrees of prior information. Our findings indicate that the stochastic inversion of the time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions compared with the corresponding priors, which in turn significantly improves knowledge of soil hydraulic properties. Overall, the results obtained clearly demonstrate the value of the information contained in time-lapse GPR data for characterizing vadose zone dynamics.

Obtaining interspecific hybrids, and molecular analysis by microsatellite markers in grapevine

The objective of this work was to assess the potential of interspecific hybridization of Vitis labruscana and Muscadinia rotundifolia by using artificial cross-pollinations. Microsatellite markers were used to confirm interspecific hybridizations and the identity of the parental genotypes. In crosses in which M. rotundifolia was used as the female parent, no true hybrids were obtained. In the reciprocal crosses, 114 seedlings were identified as true V. labruscana x M. rotundifolia hybrids. Self pollination occurred in direct and in reciprocal crosses. The crossings between 'Bordo' x 'Carlos', 'Magnolia', 'Regale' and' Roanoke', and between' Isabel' x 'Bountiful', 'Carlos', 'Magnolia', 'Regale' and 'Roanoke' were confirmed. The 15 markers evaluated showed that two M. rotundifolia parental genotypes had the same fingerprint profile, indicating a like lyplanting error. The success of hybridization depends mainly on the species and on the cultivar used as the female parent. Microsatellite markers are efficient to confirm the paternity of interspecific F1 hybrids and to determine the correct identity of M. rotundifolia cultivars.

Yield QTL analysis of Oryza sativa x O. glumaepatula introgression lines

The objective of this work was to evaluate the yield performance of two generations (BC2F2 and BC2F9) of introgression lines developed from the interspecific cross between Oryza sativa and O. glumaepatula, and to identify the SSR markers associated to yield. The wild accession RS‑16 (O. glumaepatula) was used as donor parent in the backcross with the high yielding cultivar Cica‑8 (O. sativa). A set of 114 BC2F1 introgression lines was genotyped with 141 polymorphic SSR loci distributed across the whole rice genome. Molecular analysis showed that in average 22% of the O. glumaepatula genome was introgressed into BC2F1 generation. Nine BC2F9 introgression lines had a significantly higher yield than the genitor Cica‑8, thus showing a positive genome interaction among cultivated rice and the wild O. glumaepatula. Seven QTL were identified in the overall BC2F2, with one marker interval (4879‑EST20) of great effect on yield. The alleles with positive effect on yield came from the cultivated parent Cica‑8.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.