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.

Clara cells drive eosinophil accumulation in allergic asthma.

Development of allergic asthma is a complex process involving immune, neuronal and tissue cells. In the lung, Clara cells represent a major part of the "immunomodulatory barrier" of the airway epithelium. To understand the contribution of these cells to the inflammatory outcome of asthma, disease development was assessed using an adjuvant-free ovalbumin model. Mice were sensitised with subcutaneous injections of 10 μg endotoxin-free ovalbumin in conjunction with naphthalene-induced Clara cell depletion. Clara epithelial cell depletion in the lung strongly reduced eosinophil influx, which correlated with decreased eotaxin levels and, moreover, diminished the T-helper cell type 2 inflammatory response, including interleukin (IL)-4, IL-5 and IL-13. In contrast, airway hyperresponsiveness was increased. Further investigation revealed Clara cells as the principal source of eotaxin in the lung. These findings are the first to show that Clara airway epithelial cells substantially contribute to the infiltration of eotaxin-responsive CCR3+ immune cells and augment the allergic immune response in the lung. The present study identifies Clara cells as a potential therapeutic target in inflammatory lung diseases such as allergic asthma.

MIMAS 3.0 is a Multiomics Information Management and Annotation System.

BACKGROUND: DNA sequence integrity, mRNA concentrations and protein-DNA interactions have been subject to genome-wide analyses based on microarrays with ever increasing efficiency and reliability over the past fifteen years. However, very recently novel technologies for Ultra High-Throughput DNA Sequencing (UHTS) have been harnessed to study these phenomena with unprecedented precision. As a consequence, the extensive bioinformatics environment available for array data management, analysis, interpretation and publication must be extended to include these novel sequencing data types. DESCRIPTION: MIMAS was originally conceived as a simple, convenient and local Microarray Information Management and Annotation System focused on GeneChips for expression profiling studies. MIMAS 3.0 enables users to manage data from high-density oligonucleotide SNP Chips, expression arrays (both 3'UTR and tiling) and promoter arrays, BeadArrays as well as UHTS data using MIAME-compliant standardized vocabulary. Importantly, researchers can export data in MAGE-TAB format and upload them to the EBI's ArrayExpress certified data repository using a one-step procedure. CONCLUSION: We have vastly extended the capability of the system such that it processes the data output of six types of GeneChips (Affymetrix), two different BeadArrays for mRNA and miRNA (Illumina) and the Genome Analyzer (a popular Ultra-High Throughput DNA Sequencer, Illumina), without compromising on its flexibility and user-friendliness. MIMAS, appropriately renamed into Multiomics Information Management and Annotation System, is currently used by scientists working in approximately 50 academic laboratories and genomics platforms in Switzerland and France. MIMAS 3.0 is freely available via http://multiomics.sourceforge.net/.

Meta-analysis of genome-wide association data identifies a risk locus for major mood disorders on 3p21.1.

The major mood disorders, which include bipolar disorder and major depressive disorder (MDD), are considered heritable traits, although previous genetic association studies have had limited success in robustly identifying risk loci. We performed a meta-analysis of five case-control cohorts for major mood disorder, including over 13,600 individuals genotyped on high-density SNP arrays. We identified SNPs at 3p21.1 associated with major mood disorders (rs2251219, P = 3.63 x 10(-8); odds ratio = 0.87; 95% confidence interval, 0.83-0.92), with supportive evidence for association observed in two out of three independent replication cohorts. These results provide an example of a shared genetic susceptibility locus for bipolar disorder and MDD.

Subclinical peripheral synovitis detected by echography in patients with axial Spondyloarthritis

Background: patients with axial Spondyloarthritis (SD), even withoutany obvious peripheral joint synovitis, often complain of pain in thejoints of arms and legs. Several musculoskeletal ultrasound (US)scores developed in rheumatoid arthritis have demonstrated theircapacity of discovering subclinical synovitis which were relevant interm of disease activity and for treatment strategies. None of thesescores however have been, to our knowledge, applied tospondyloarthritis patients.Objectives: to determine if subclinical synovitis can be detected byechography in patients with SD and if these synovitis are relevantcompared with RA and controls.Methods: the Swiss Sonography in Arthritis and Rheumatism(SONAR) group has developed a reproducible semi-quantitative scorefor RA using OMERACT criteria for synovitis. The score includes Bmode and Doppler mode. 35 out of 40 enrolled SD patients fulfillingthe 2010 diagnostic criteria were evaluated according to the SONARscore. In none of them, peripheral synovitis was clearly demonstrated,although some have or reported recurrent peripheral joint pain. Thescore was also applied to 20 matched controls and 40 consecutive RApatients (RA). 19 of them were in remission (DAS: <2.6), 10 with alow activity (DAS: 2.6 <>3.4) and 11 with a moderate activity disease(DAS: 3.5 <>5.1). All the patients and the controls had a completeclinical, biological and auto-evaluation assessment (joint pain andswelling counts, DAS28, HAQ, BASDAI BASMI, BASFI, m-SACRAH).The ultra-sonographer was blind to all these parameters.Results: a B mode score >8, was set up as a cut-off value forsignificant synovitis as only 10% of the controls (median: 5.9 ± 2.2)and 90% of active RA had a higher score .34% of SD had significantsynovitis which remained mostly mild. Their median B mode score(12 ± 1.6) was higher but not significantly than in remission Ra (7.1 ±3.4). Only active RA (DAS >3.5) had significant higher echographicscores: B mode (17 ± 11), Doppler score and cumulative score forsynovitis grade >1. BASDAI, BASFI, BASMI, m-SACRAH, DAS28 andCRP were not significantly different in SD patients with or withoutsynovitis.Conclusions: some patients with axial Spondyloarthritis havesubclinical but significant peripheral synovitis detected by echography.The impact of these synovitis remains uncertain as their presencedoes not seem to significantly influence disease activity and functionevaluation tools.

Changes associated with laboratory rearing in antennal sensilla patterns of Triatoma infestans, Rhodnius prolixus, and Rhodnius pallescens (Hemiptera, Reduviidae, Triatominae)

We examined changes in the array of antennal sensilla of three species of Triatominae (Triatoma infestans, Rhodnius prolixus, and R. pallescens) following their establishment for different periods in laboratory culture. In each case, the laboratory colonies were compared with conspecific samples taken directly from the field, by quantitative analysis of the sensilla arrays on the three distal segments of the antenna in terms of the densities of three types of chemoreceptors (basiconics and thick and thin walled trichoids) and one type of mechanoreceptor (bristles). Sensilla densities were compared by ANOVA or non-parametric tests, and by multivariate discriminant analysis. Strains of the same species reared in different laboratories showed significant differences in their sensilla arrays, especially when compared to field-collected material from the same geographic origin. A Bolivian strain of T. infestans reared in the laboratory for 15 years and fed at monthly intervals, showed greatest differences from its conspecific wild forms, especially in terms of reductions in the number of chemoreceptors. By contrast, an Argentine strain of T. infestans reared for 25 years in the laboratory and fed weekly, showed a relative increase in the density of mechanoreceptors. A Colombian strain of R. prolixus reared for 20 years and fed weekly or fortnightly, showed only modest differences in the sensilla array when compared to its wild populations from the same area. However, a Colombian strain of R. pallescens reared for 12 years and fed fortnightly, did show highly significant reductions in one form of chemoreceptor compared to its conspecific wild populations. For all populations, multivariate analysis clearly discriminated between laboratory and field collected specimens, suggesting that artificial rearing can lead to modifications in the sensory array. This not only supports the idea of morphological plasticity in these species, but also suggests caution in the use of long-established laboratory material for experimental studies designed to extrapolate the natural behaviour and physiology of these species.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

Quantifying network properties in multi-electrode recordings: spatiotemporal characterization and inter-trial variation of evoked gamma oscillations in mouse somatosensory cortex in vitro.

Linking the structural connectivity of brain circuits to their cooperative dynamics and emergent functions is a central aim of neuroscience research. Graph theory has recently been applied to study the structure-function relationship of networks, where dynamical similarity of different nodes has been turned into a "static" functional connection. However, the capability of the brain to adapt, learn and process external stimuli requires a constant dynamical functional rewiring between circuitries and cell assemblies. Hence, we must capture the changes of network functional connectivity over time. Multi-electrode array data present a unique challenge within this framework. We study the dynamics of gamma oscillations in acute slices of the somatosensory cortex from juvenile mice recorded by planar multi-electrode arrays. Bursts of gamma oscillatory activity lasting a few hundred milliseconds could be initiated only by brief trains of electrical stimulations applied at the deepest cortical layers and simultaneously delivered at multiple locations. Local field potentials were used to study the spatio-temporal properties and the instantaneous synchronization profile of the gamma oscillatory activity, combined with current source density (CSD) analysis. Pair-wise differences in the oscillation phase were used to determine the presence of instantaneous synchronization between the different sites of the circuitry during the oscillatory period. Despite variation in the duration of the oscillatory response over successive trials, they showed a constant average power, suggesting that the rate of expenditure of energy during the gamma bursts is consistent across repeated stimulations. Within each gamma burst, the functional connectivity map reflected the columnar organization of the neocortex. Over successive trials, an apparently random rearrangement of the functional connectivity was observed, with a more stable columnar than horizontal organization. This work reveals new features of evoked gamma oscillations in developing cortex.

Reverse transcription quantitative real-time polymerase chain reaction reference genes in the spared nerve injury model of neuropathic pain : validation and literature search

La douleur neuropathique est définie comme une douleur causée par une lésion du système nerveux somato-sensoriel. Elle se caractérise par des douleurs exagérées, spontanées, ou déclenchées par des stimuli normalement non douloureux (allodynie) ou douloureux (hyperalgésie). Bien qu'elle concerne 7% de la population, ses mécanismes biologiques ne sont pas encore élucidés. L'étude des variations d'expressions géniques dans les tissus-clés des voies sensorielles (notamment le ganglion spinal et la corne dorsale de la moelle épinière) à différents moments après une lésion nerveuse périphérique permettrait de mettre en évidence de nouvelles cibles thérapeutiques. Elles se détectent de manière sensible par reverse transcription quantitative real-time polymerase chain reaction (RT- qPCR). Pour garantir des résultats fiables, des guidelines ont récemment recommandé la validation des gènes de référence utilisés pour la normalisation des données ("Minimum information for publication of quantitative real-time PCR experiments", Bustin et al 2009). Après recherche dans la littérature des gènes de référence fréquemment utilisés dans notre modèle de douleur neuropathique périphérique SNI (spared nerve injury) et dans le tissu nerveux en général, nous avons établi une liste de potentiels bons candidats: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) et L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) et hydroxymethyl-bilane synthase (HMBS). Nous avons évalué la stabilité d'expression de ces gènes dans le ganglion spinal et dans la corne dorsale à différents moments après la lésion nerveuse (SNI) en calculant des coefficients de variation et utilisant l'algorithme geNorm qui compare les niveaux d'expression entre les différents candidats et détermine la paire de gènes restante la plus stable. Il a aussi été possible de classer les gènes selon leur stabilité et d'identifier le nombre de gènes nécessaires pour une normalisation la plus précise. Les gènes les plus cités comme référence dans le modèle SNI ont été GAPDH, HMBS, Actb, HPRT1 et 18S. Seuls HPRT1 and 18S ont été précédemment validés dans des arrays de RT-qPCR. Dans notre étude, tous les gènes testés dans le ganglion spinal et dans la corne dorsale satisfont au critère de stabilité exprimé par une M-value inférieure à 1. Par contre avec un coefficient de variation (CV) supérieur à 50% dans le ganglion spinal, 18S ne peut être retenu. La paire de gènes la plus stable dans le ganglion spinal est HPRT1 et Actb et dans la corne dorsale il s'agit de RPL29 et RPL13a. L'utilisation de 2 gènes de référence stables suffit pour une normalisation fiable. Nous avons donc classé et validé Actb, RPL29, RPL13a, HMBS, GAPDH, HPRT1 et 18S comme gènes de référence utilisables dans la corne dorsale pour le modèle SNI chez le rat. Dans le ganglion spinal 18S n'a pas rempli nos critères. Nous avons aussi déterminé que la combinaison de deux gènes de référence stables suffit pour une normalisation précise. Les variations d'expression génique de potentiels gènes d'intérêts dans des conditions expérimentales identiques (SNI, tissu et timepoints post SNI) vont pouvoir se mesurer sur la base d'une normalisation fiable. Non seulement il sera possible d'identifier des régulations potentiellement importantes dans la genèse de la douleur neuropathique mais aussi d'observer les différents phénotypes évoluant au cours du temps après lésion nerveuse.

Impact of normalization on miRNA microarray expression profiling.

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.

Molecular risk assessment of BIG 1-98 participants by expression profiling using RNA from archival tissue.

Background: The purpose of the work reported here is to test reliable molecular profiles using routinely processed formalin-fixed paraffin-embedded (FFPE) tissues from participants of the clinical trial BIG 1-98 with a median follow-up of 60 months. Methods: RNA from fresh frozen (FF) and FFPE tumor samples of 82 patients were used for quality control, and independent FFPE tissues of 342 postmenopausal participants of BIG 1-98 with ER-positive cancer were analyzed by measuring prospectively selected genes and computing scores representing the functions of the estrogen receptor (eight genes, ER_8), the progesterone receptor (five genes, PGR_5), Her2 (two genes, HER2_2), and proliferation (ten genes, PRO_10) by quantitative reverse transcription PCR (qRT-PCR) on TaqMan Low Density Arrays. Molecular scores were computed for each category and ER_8, PGR_5, HER2_2, and PRO_10 scores were combined into a RISK_25 score. Results: Pearson correlation coefficients between FF- and FFPE-derived scores were at least 0.94 and high concordance was observed between molecular scores and immunohistochemical data. The HER2_2, PGR_ 5, PRO_10 and RISK_25 scores were significant predictors of disease free-survival (DFS) in univariate Cox proportional hazard regression. PRO_10 and RISK_25 scores predicted DFS in patients with histological grade II breast cancer and in lymph node positive disease. The PRO_10 and PGR_ 5 scores were independent predictors of DFS in multivariate Cox regression models incorporating clinical risk indicators; PRO_10 outperformed Ki-67 labeling index in multivariate Cox proportional hazard analyses. Conclusions: Scores representing the endocrine responsiveness and proliferation status of breast cancers were developed from gene expression analyses based on RNA derived from FFPE tissues. The validation of the molecular scores with tumor samples of participants of the BIG 1-98 trial demonstrates that such scores can serve as independent prognostic factors to estimate disease free survival (DFS) in postmenopausal patients with estrogen receptor positive breast cancer.

Emergence of dhfrXVb and blaCARB-4 gene cassettes in class 1 integrons from clinical Pseudomonas aeruginosa isolated in Amazon region

Integrons play a role in horizontal acquisition and expression of genes, as well as gene reservoir, contributing for the resistance phenotype, particularly relevant to bacteria of clinical importance. We aimed to determine the composition and the organization of the class 1 integron variable region present in Pseudomonas aeruginosa clinical isolates from Brazil. Strains carrying class 1 integrons were resistant to the majority of antibiotics tested, except to imipenem and ceftazidime. Sequence analysis of the integron variable region revealed the presence of the blaCARB-4 gene into two distinct cassette arrays: aacA4-dhfrXVb-blaCARB-4 and aadB-aacA4-blaCARB-4 . dhfrXVb gene cassette, which is rare in Brazil and in P. aeruginosa species, was found in one isolate. PFGE analysis showed the spread of blaCARB-4 among P. aeruginosa clones. The occurrence of blaCARB-4 and dhfrXVb in Brazil may contribute for developing resistance to clinically important antibiotics, and shows a diversified scenarium of these elements occurring in Amazon clinical settings, where no study about integron dinamycs was performed to date.

Host and invader impact of transfer of the clc genomic island into Pseudomonas aeruginosa PAO1

Genomic islands, large potentially mobile regions of bacterial chromosomes, are a major contributor to bacteria evolution. Here, we investigated the fitness cost and phenotypic differences between the bacterium Pseudomonas aeruginosa PAO1 and a derivative carrying one integrated copy of the clc element, a 103-kb genomic island [and integrative and conjugative element (ICE)] originating in Pseudomonas sp. strain B13 and a close relative of genomic islands found in clinical and environmental isolates of P. aeruginosa. By using a combination of whole genome transcriptome profiling, phenotypic arrays, competition experiments, and biofilm formation studies, only few differences became apparent, such as reduced biofilm growth and fourfold stationary phase repression of genes involved in acetoin metabolism in PAO1 containing the clc element. In contrast, PAO1 carrying the clc element acquired the capacity to grow on 3-chlorobenzoate and 2-aminophenol as sole carbon and energy substrates. No fitness loss >1% was detectable in competition experiments between PAO1 and PAO1 carrying the clc element. The genes from the clc element were not silent in PAO1, and excision was observed, although transfer of clc from PAO1 to other recipient bacteria was reduced by two orders of magnitude. Our results indicate that newly acquired mobile DNA not necessarily invoke an important fitness cost on their host. Absence of immediate detriment to the host may have contributed to the wide distribution of genomic islands like clc in bacterial genomes

High-density electric source imaging (esi) in focal epilepsy: a prospective study of 150 operated patients

Purpose: EEG is mandatory in the diagnosis of the epilepsy syndrome. However, its potential as imaging tool is still under estimated. In the present study, we aim to determine the prerequisites of maximal benefit of electric source imaging (ESI) to localize the irritative zone in patients with focal epilepsy. Methods: One hundred fifty patients suffering from focal epilepsy and with minimum 1 year postoperative follow-up were studied prospectively and blinded to the underlying diagnosis. We evaluated the influence of two important factors on sensitivity and specificity of ESI: the number of electrodes (low resolution, LR-ESI: <30 versus high resolution, HR-ESI: 128-256 electrodes), and the use of individual MRI (i-MRI) versus template MRI (t-MRI) as the head model. Findings: ESI had a sensitivity of 85% and a specificity of 87% when HR-ESI with i-MRI was used. Using LR-ESI, sensitivity decreased to 68%, or even 57% when only t-MRI was available. The sensitivity of HR-ESI/i-MRI compared favorably with those of MRI (76%), PET (69%) and ictal/interictal SPECT (64%). Interpretation: This study on a large patient group shows excellent sensitivity and specificity of ESI if 128 EEG channels or more are used for ESI and if the results are coregistered to the patient's individual MRI. Localization precision is as high as or even higher than established brain imagery techniques. HR-ESI appears to be a valuable additional imaging tool, given that larger electrode arrays are easily and rapidly applied with modern EEG equipment and that structural MRI is nearly always available for these patients.

Extremal properties of certain risk models

Cette thèse s'intéresse à étudier les propriétés extrémales de certains modèles de risque d'intérêt dans diverses applications de l'assurance, de la finance et des statistiques. Cette thèse se développe selon deux axes principaux, à savoir: Dans la première partie, nous nous concentrons sur deux modèles de risques univariés, c'est-à- dire, un modèle de risque de déflation et un modèle de risque de réassurance. Nous étudions le développement des queues de distribution sous certaines conditions des risques commun¬s. Les principaux résultats sont ainsi illustrés par des exemples typiques et des simulations numériques. Enfin, les résultats sont appliqués aux domaines des assurances, par exemple, les approximations de Value-at-Risk, d'espérance conditionnelle unilatérale etc. La deuxième partie de cette thèse est consacrée à trois modèles à deux variables: Le premier modèle concerne la censure à deux variables des événements extrême. Pour ce modèle, nous proposons tout d'abord une classe d'estimateurs pour les coefficients de dépendance et la probabilité des queues de distributions. Ces estimateurs sont flexibles en raison d'un paramètre de réglage. Leurs distributions asymptotiques sont obtenues sous certaines condi¬tions lentes bivariées de second ordre. Ensuite, nous donnons quelques exemples et présentons une petite étude de simulations de Monte Carlo, suivie par une application sur un ensemble de données réelles d'assurance. L'objectif de notre deuxième modèle de risque à deux variables est l'étude de coefficients de dépendance des queues de distributions obliques et asymétriques à deux variables. Ces distri¬butions obliques et asymétriques sont largement utiles dans les applications statistiques. Elles sont générées principalement par le mélange moyenne-variance de lois normales et le mélange de lois normales asymétriques d'échelles, qui distinguent la structure de dépendance de queue comme indiqué par nos principaux résultats. Le troisième modèle de risque à deux variables concerne le rapprochement des maxima de séries triangulaires elliptiques obliques. Les résultats théoriques sont fondés sur certaines hypothèses concernant le périmètre aléatoire sous-jacent des queues de distributions. -- This thesis aims to investigate the extremal properties of certain risk models of interest in vari¬ous applications from insurance, finance and statistics. This thesis develops along two principal lines, namely: In the first part, we focus on two univariate risk models, i.e., deflated risk and reinsurance risk models. Therein we investigate their tail expansions under certain tail conditions of the common risks. Our main results are illustrated by some typical examples and numerical simu¬lations as well. Finally, the findings are formulated into some applications in insurance fields, for instance, the approximations of Value-at-Risk, conditional tail expectations etc. The second part of this thesis is devoted to the following three bivariate models: The first model is concerned with bivariate censoring of extreme events. For this model, we first propose a class of estimators for both tail dependence coefficient and tail probability. These estimators are flexible due to a tuning parameter and their asymptotic distributions are obtained under some second order bivariate slowly varying conditions of the model. Then, we give some examples and present a small Monte Carlo simulation study followed by an application on a real-data set from insurance. The objective of our second bivariate risk model is the investigation of tail dependence coefficient of bivariate skew slash distributions. Such skew slash distributions are extensively useful in statistical applications and they are generated mainly by normal mean-variance mixture and scaled skew-normal mixture, which distinguish the tail dependence structure as shown by our principle results. The third bivariate risk model is concerned with the approximation of the component-wise maxima of skew elliptical triangular arrays. The theoretical results are based on certain tail assumptions on the underlying random radius.