Athos Antoniades

Genome-wide association study of recurrent major depressive disorder in two European case-control cohorts.

Major depressive disorder (MDD) is a highly prevalent disorder with substantial heritability. Heritability has been shown to be substantial and higher in the variant of MDD characterized by recurrent episodes of depression. Genetic studies have thus far failed to identify clear and consistent evidence of genetic risk factors for MDD. We conducted a genome-wide association study (GWAS) in two independent datasets. The first GWAS was performed on 1022 recurrent MDD patients and 1000 controls genotyped on the Illumina 550 platform. The second was conducted on 492 recurrent MDD patients and 1052 controls selected from a population-based collection, genotyped on the Affymetrix 5.0 platform. Neither GWAS identified any SNP that achieved GWAS significance. We obtained imputed genotypes at the Illumina loci for the individuals genotyped on the Affymetrix platform, and performed a meta-analysis of the two GWASs for this common set of approximately half a million SNPs. The meta-analysis did not yield genome-wide significant results either. The results from our study suggest that SNPs with substantial odds ratio are unlikely to exist for MDD, at least in our datasets and among the relatively common SNPs genotyped or tagged by the half-million-loci arrays. Meta-analysis of larger datasets is warranted to identify SNPs with smaller effects or with rarer allele frequencies that contribute to the risk of MDD.

A Genome-Wide Association Study of Neuroticism in a Population-Based Sample

Neuroticism is a moderately heritable personality trait considered to be a risk factor for developing major depression, anxiety disorders and dementia. We performed a genome-wide association study in 2,235 participants drawn from a population-based study of neuroticism, making this the largest association study for neuroticism to date. Neuroticism was measured by the Eysenck Personality Questionnaire. After Quality Control, we analysed 430,000 autosomal SNPs together with an additional 1.2 million SNPs imputed with high quality from the Hap Map CEU samples. We found a very small effect of population stratification, corrected using one principal component, and some cryptic kinship that required no correction. NKAIN2 showed suggestive evidence of association with neuroticism as a main effect (p<10−6) and GPC6 showed suggestive evidence for interaction with age (p≈10−7). We found support for one previously-reported association (PDE4D), but failed to replicate other recent reports. These results suggest common SNP variation does not strongly influence neuroticism. Our study was powered to detect almost all SNPs explaining at least 2% of heritability, and so our results effectively exclude the existence of loci having a major effect on neuroticism.

Linked2Safety: A secure linked data medical information space for semantically-interconnecting EHRs advancing patients' safety in medical research

Electronic Health Records (EHRs) contain an increasing wealth of medical information. They have the potential to help significantly in advancing medical research, as well as improve health policies, providing society with additional benefits. However, the European healthcare information space is fragmented due to the lack of legal and technical standards, cost effective platforms, and sustainable business models. The vision of Linked2Safety is to advance clinical practice and accelerate medical research, by providing pharmaceutical companies, healthcare professionals and patients with an innovative secure semantic interoperability framework facilitating the efficient and homogenized access to anonymised distributed EHRs in an aggregate form that enables merging multiple data sources into a single analyses. In this paper a first public introduction to the project is provided along with a clear definition of the problems, and proposed architecture. Three usage scenarios are used to demonstrate the potential impact of the outcomes of the project.

A Virtual Emergency Telemedicine Serious Game in Medical Training: A Quantitative, Professional Feedback-Informed Evaluation Study.

Background Serious games involving virtual patients in medical education can provide a controlled setting within which players can learn in an engaging way, while avoiding the risks associated with real patients. Moreover, serious games align with medical students’ preferred learning styles. The Virtual Emergency TeleMedicine (VETM) game is a simulation-based game that was developed in collaboration with the mEducator Best Practice network in response to calls to integrate serious games in medical education and training. The VETM game makes use of data from an electrocardiogram to train practicing doctors, nurses, or medical students for problem-solving in real-life clinical scenarios through a telemedicine system and virtual patients. The study responds to two gaps: the limited number of games in emergency cardiology and the lack of evaluations by professionals. Objective The objective of this study is a quantitative, professional feedback-informed evaluation of one scenario of VETM, involving cardiovascular complications. The study has the following research question: “What are professionals’ perceptions of the potential of the Virtual Emergency Telemedicine game for training people involved in the assessment and management of emergency cases?” Methods The evaluation of the VETM game was conducted with 90 professional ambulance crew nursing personnel specializing in the assessment and management of emergency cases. After collaboratively trying out one VETM scenario, participants individually completed an evaluation of the game (36 questions on a 5-point Likert scale) and provided written and verbal comments. The instrument assessed six dimensions of the game: (1) user interface, (2) difficulty level, (3) feedback, (4) educational value, (5) user engagement, and (6) terminology. Data sources of the study were 90 questionnaires, including written comments from 51 participants, 24 interviews with 55 participants, and 379 log files of their interaction with the game. Results Overall, the results were positive in all dimensions of the game that were assessed as means ranged from 3.2 to 3.99 out of 5, with user engagement receiving the highest score (mean 3.99, SD 0.87). Users’ perceived difficulty level received the lowest score (mean 3.20, SD 0.65), a finding which agrees with the analysis of log files that showed a rather low success rate (20.6%). Even though professionals saw the educational value and usefulness of the tool for pre-hospital emergency training (mean 3.83, SD 1.05), they identified confusing features and provided input for improving them. Conclusions Overall, the results of the professional feedback-informed evaluation of the game provide a strong indication of its potential as an educational tool for emergency training. Professionals’ input will serve to improve the game. Further research will aim to validate VETM, in a randomized pre-test, post-test control group study to examine possible learning gains in participants’ problem-solving skills in treating a patient’s symptoms in an emergency situation.

Gene variants of adhesion molecules act as modifiers of disease severity in MS

Objective: To assess the potential effect of variants in genes encoding molecules that are implicated in leukocyte trafficking into the CNS on the clinical phenotype of multiple sclerosis (MS). Methods: A total of 389 Greek MS cases and 336 controls were recruited in 3 MS centers from Cyprus and Greece. We genotyped 147 tagging single nucleotide polymorphisms (SNPs) in 9 genes encoding for P-selectin (SELP), integrins (ITGA4, ITGB1, and ITGB7), adhesion molecules (ICAM1, VCAM1, and MADCAM1), fibronectin 1 (FN1), and osteopontin (SPP1) involved in lymphocyte adhesion and trafficking into the CNS. Clinical end points of the study were age at MS onset and MS severity as measured by the Multiple Sclerosis Severity Score. Permutation testing was applied to all analyses. Results: SNPs rs6721763 of the ITGA4 and rs6532040 of the SPP1 were found to significantly influence disease severity (permutation p values: 3.00e-06 and 0.009884, respectively). SNP rs1250249 of the FN1 had a dose-dependent effect on age at disease onset (permutation p value: 0.0002). Conclusions: This study provides evidence implicating variants encoding adhesion molecules, responsible for lymphocyte adhesion and trafficking within the CNS, as modifiers of MS disease severity. These genetic biomarkers, which can be available at the time of diagnosis, may be used to assess the biological aggressiveness of the disease and thus guide decisions on treatment.

Two hybrid evolutionary algorithms for the rectilinear Steiner arborescence problem

Given a collection of points in the first quadrant, a rectilinear Steiner arborescence is a tree made up of horizontal and vertical line segments on the points and the origin in which every path from the origin leads only up and to the right. The minimum rectilinear Steiner arborescence problem seeks such a tree of minimum total length.A greedy heuristic due to Rao et al. [13] builds short arborescences and can be implemented to require time that is O(n log n). Two evolutionary encodings of rectilinear Steiner arborescences represent them as permutations of points and as strings of perturbations of point locations. A decoder in the style of Prims algorithm identifies the arborescence that a permutation represents; the heuristic of Rao et al. identifies the arborescence corresponding to a string of perturbations.In tests on twenty instances of the problem of 50 to 250 points, a genetic algorithm using the permutation coding is unable to compete with the greedy heuristic, but a GA using the perturbation coding almost always improves on the heuristics results, though in general the improvement is small.

Type 2 Diabetes Susceptibility in the Greek-Cypriot Population: Replication of Associations with TCF7L2, FTO, HHEX, SLC30A8 and IGF2BP2 Polymorphisms

Type 2 diabetes (T2D) has been the subject of numerous genetic studies in recent years which revealed associations of the disease with a large number of susceptibility loci. We hereby initiate the evaluation of T2D susceptibility loci in the Greek-Cypriot population by performing a replication case-control study. One thousand and eighteen individuals (528 T2D patients, 490 controls) were genotyped at 21 T2D susceptibility loci, using the allelic discrimination method. Statistically significant associations of T2D with five of the tested single nucleotide polymorphisms (SNPs) (TCF7L2 rs7901695, FTO rs8050136, HHEX rs5015480, SLC30A8 rs13266634 and IGF2BP2 rs4402960) were observed in this study population. Furthermore, 14 of the tested SNPs had odds ratios (ORs) in the same direction as the previously published studies, suggesting that these variants can potentially be used in the Greek-Cypriot population for predictive testing of T2D. In conclusion, our findings expand the genetic assessment of T2D susceptibility loci and reconfirm five of the worldwide established loci in a distinct, relatively small, newly investigated population.

Nature and Consequences of Biological Reductionism for the Immunological Study of Infectious Diseases

Evolution has conserved “economic” systems that perform many functions, faster or better, with less. For example, three to five leukocyte types protect from thousands of pathogens. To achieve so much with so little, biological systems combine their limited elements, creating complex structures. Yet, the prevalent research paradigm is reductionist. Focusing on infectious diseases, reductionist and non-reductionist views are here described. The literature indicates that reductionism is associated with information loss and errors, while non-reductionist operations can extract more information from the same data. When designed to capture one-to-many/many-to-one interactions—including the use of arrows that connect pairs of consecutive observations—non-reductionist (spatial–temporal) constructs eliminate data variability from all dimensions, except along one line, while arrows describe the directionality of temporal changes that occur along the line. To validate the patterns detected by non-reductionist operations, reductionist procedures are needed. Integrated (non-reductionist and reductionist) methods can (i) distinguish data subsets that differ immunologically and statistically; (ii) differentiate false-negative from -positive errors; (iii) discriminate disease stages; (iv) capture in vivo, multilevel interactions that consider the patient, the microbe, and antibiotic-mediated responses; and (v) assess dynamics. Integrated methods provide repeatable and biologically interpretable information.

A computationally fast measure of epistasis for 2 SNPs and a categorical phenotype

Complex diseases may be caused by interactions or combined effects between multiple genetic and environmental factors. One of the main limitations of testing for interaction between genetic loci in large whole genome studies is the high computational cost of performing such analyses. In this study a new methodology for interaction testing (commonly referred to in genetics as the epistatic effect) between two single nucleotide polymorphisms (SNPs) and a categorical phenotype is presented. It is shown that it provides reasonable approximations with a significantly shorter run time. The proposed measure based on the Pearsons chi-square additive property is compared to fitting a logistic regression model on a randomly selected subset of 218 SNP loci from a study that included 550,000 SNPs). For each possible pair of SNPs a chi-square test for the epistatic effect on case-control status is estimated by fitting a logistic regression model, and compared to the results of the proposed method. Results indicate strong agreement (Pearsons correlation r>0.95) while the proposed method is found to be 20 times faster. This provides a significant pragmatic advantage for the proposed method since the number of tests for epistasis can now be increased by a factor of 20 while the computational cost remains the same.

Discovering genetic polymorphism associated with gene expression levels across the whole genome

Genetic differences have been shown to contribute to gene expression variability. A complete evaluation of the associations between a whole genome scan with 550k Single Nucleotide Polymorphisms (SNPs) and 54k detectable expression levels (probesets) was performed on 176 human peripheral blood samples. The results are presented along with visualizations that reveal cis and trans gene expression regulatory effects. The algorithmic approach followed utilized a distributed computational system. The analysis was performed using a linear regression adjusting for all relevant covariates. Permutation testing on a random subset of the top results provided an indication of the significance levels adjusted for multiple testing and the non independence of SNPs due to linkage disequilibrium. The database of the produced results can be used as a resource to assess the functional impact of genetic polymorphisms to gene expression regulation. This resource is applicable across all disease areas.