A novel approach to simulate gene-environment interactions in complex diseases

Background: Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. Results: We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. Conclusions: By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study

Does Community Context Have an Important Impact on Divorce Risk? A Fixed-Effects Study of Twenty Norwegian First-Marriage Cohorts

The decision to divorce may be affected by the characteristics of the local community. Community characteristics may be barriers to divorce, or they may increase the attractiveness of divorcing (e.g., access to a good remarriage market), but our knowledge of such influences is sparse. This study examines two such community-level factors: socio-economic conditions and the local marriage market. In this study, discrete-time hazard models with community-level fixed effects are estimated using register-based data on Norwegian first marriages during the period from 1980 to 1999, with longitudinal information on both the community and couple levels (N = 283,493). The results show that there are important community-level influences on couples’ divorce risk, but these change dramatically when fixed effects are introduced

A novel parametric approach to mine gene regulatory relationship from microarray datasets

<p>Abstract</p> <p>Background</p> <p>Microarray has been widely used to measure the gene expression level on the genome scale in the current decade. Many algorithms have been developed to reconstruct gene regulatory networks based on microarray data. Unfortunately, most of these models and algorithms focus on global properties of the expression of genes in regulatory networks. And few of them are able to offer intuitive parameters. We wonder whether some simple but basic characteristics of microarray datasets can be found to identify the potential gene regulatory relationship.</p> <p>Results</p> <p>Based on expression correlation, expression level variation and vectors derived from microarray expression levels, we first introduced several novel parameters to measure the characters of regulating gene pairs. Subsequently, we used the naïve Bayesian network to integrate these features as well as the functional co-annotation between transcription factors and their target genes. Then, based on the character of time-delay from the expression profile, we were able to predict the existence and direction of the regulatory relationship respectively.</p> <p>Conclusions</p> <p>Several novel parameters have been proposed and integrated to identify the regulatory relationship. This new model is proved to be of higher efficacy than that of individual features. It is believed that our parametric approach can serve as a fast approach for regulatory relationship mining.</p

Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England

The SARS-CoV-2 lineage B.1.1.7, designated variant of concern (VOC) 202012/01 by Public Health England1, was first identified in the UK in late summer to early autumn 20202. Whole-genome SARS-CoV-2 sequence data collected from community-based diagnostic testing for COVID-19 show an extremely rapid expansion of the B.1.1.7 lineage during autumn 2020, suggesting that it has a selective advantage. Here we show that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S gene target failures (SGTF) in community-based diagnostic PCR testing. Analysis of trends in SGTF and non-SGTF case numbers in local areas across England shows that B.1.1.7 has higher transmissibility than non-VOC lineages, even if it has a different latent period or generation time. The SGTF data indicate a transient shift in the age composition of reported cases, with cases of B.1.1.7 including a larger share of under 20-year-olds than non-VOC cases. We estimated time-varying reproduction numbers for B.1.1.7 and co-circulating lineages using SGTF and genomic data. The best-supported models did not indicate a substantial difference in VOC transmissibility among different age groups, but all analyses agreed that B.1.1.7 has a substantial transmission advantage over other lineages, with a 50% to 100% higher reproduction number

Family social environment in childhood and self-rated health in young adulthood

<p>Abstract</p> <p>Background</p> <p>Family social support, as a form of social capital, contributes to social health disparities at different age of life. In a life-course epidemiological perspective, the aims of our study were to examine the association between self-reported family social environment during childhood and self-reported health in young adulthood and to assess the role of family functioning during childhood as a potential mediating factor in explaining the association between family breakup in childhood and self-reported health in young adulthood.</p> <p>Methods</p> <p>We analyzed data from the first wave of the Health, Inequalities and Social Ruptures Survey (SIRS), a longitudinal health and socio-epidemiological survey of a random sample of 3000 households initiated in the Paris metropolitan area in 2005. Sample-weighted logistic regression analyses were performed to determine the association between the quality of family social environment in childhood and self-rated health (overall health, physical health and psychological well-being) in young adults (n = 1006). We used structural equation model to explore the mediating role of the quality of family functioning in childhood in the association between family breakup in childhood and self-rated health in young adulthood.</p> <p>Results</p> <p>The multivariate results support an association between a negative family social environment in childhood and poor self-perceived health in adulthood. The association found between parental separation or divorce in childhood and poor self-perceived health in adulthood was mediated by parent-child relationships and by having witnessed interparental violence during childhood.</p> <p>Conclusion</p> <p>These results argue for interventions that enhance family cohesion, particularly after family disruptions during childhood, to promote health in young adulthood.</p

Comparison of two protective lung ventilatory regimes on oxygenation during one-lung ventilation: a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>The efficacy of protective ventilation in acute lung injury has validated its use in the operating room for patients undergoing thoracic surgery with one-lung ventilation (OLV). The purpose of this study was to investigate the effects of two different modes of ventilation using low tidal volumes: pressure controlled ventilation (PCV) vs. volume controlled ventilation (VCV) on oxygenation and airway pressures during OLV.</p> <p>Methods</p> <p>We studied 41 patients scheduled for thoracoscopy surgery. After initial two-lung ventilation with VCV patients were randomly assigned to one of two groups. In one group OLV was started with VCV (tidal volume 6 mL/kg, PEEP 5) and after 30 minutes ventilation was switched to PCV (inspiratory pressure to provide a tidal volume of 6 mL/kg, PEEP 5) for the same time period. In the second group, ventilation modes were performed in reverse order. Airway pressures and blood gases were obtained at the end of each ventilatory mode.</p> <p>Results</p> <p>PaO₂, PaCO₂and alveolar-arterial oxygen difference did not differ between PCV and VCV. Peak airway pressure was significantly lower in PCV compared with VCV (19.9 ± 3.8 cmH₂O vs 23.1 ± 4.3 cmH₂O; p < 0.001) without any significant differences in mean and plateau pressures.</p> <p>Conclusions</p> <p>In patients with good preoperative pulmonary function undergoing thoracoscopy surgery, the use of a protective lung ventilation strategy with VCV or PCV does not affect the oxygenation. PCV was associated with lower peak airway pressures.</p

Rapid Sampling of Molecular Motions with Prior Information Constraints

Proteins are active, flexible machines that perform a range of different functions. Innovative experimental approaches may now provide limited partial information about conformational changes along motion pathways of proteins. There is therefore a need for computational approaches that can efficiently incorporate prior information into motion prediction schemes. In this paper, we present PathRover, a general setup designed for the integration of prior information into the motion planning algorithm of rapidly exploring random trees (RRT). Each suggested motion pathway comprises a sequence of low-energy clash-free conformations that satisfy an arbitrary number of prior information constraints. These constraints can be derived from experimental data or from expert intuition about the motion. The incorporation of prior information is very straightforward and significantly narrows down the vast search in the typically high-dimensional conformational space, leading to dramatic reduction in running time. To allow the use of state-of-the-art energy functions and conformational sampling, we have integrated this framework into Rosetta, an accurate protocol for diverse types of structural modeling. The suggested framework can serve as an effective complementary tool for molecular dynamics, Normal Mode Analysis, and other prevalent techniques for predicting motion in proteins. We applied our framework to three different model systems. We show that a limited set of experimentally motivated constraints may effectively bias the simulations toward diverse predicates in an outright fashion, from distance constraints to enforcement of loop closure. In particular, our analysis sheds light on mechanisms of protein domain swapping and on the role of different residues in the motion

The link between volcanism and plutonism in epizonal magma systems; high-precision U–Pb zircon geochronology from the Organ Mountains caldera and batholith, New Mexico

The Organ Mountains caldera and batholith expose the volcanic and epizonal plutonic record of an Eocene caldera complex. The caldera and batholith are well exposed, and extensive previous mapping and geochemical analyses have suggested a clear link between the volcanic and plutonic sections, making this an ideal location to study magmatic processes associated with caldera volcanism. Here we present high-precision thermal ionization mass spectrometry U–Pb zircon dates from throughout the caldera and batholith, and use these dates to test and improve existing petrogenetic models. The new dates indicate that Eocene volcanic and plutonic rocks in the Organ Mountains formed from ~44 to 34 Ma. The three largest caldera-related tuff units yielded weighted mean [superscript 206]Pb/[superscript 238]U dates of 36.441 ± 0.020 Ma (Cueva Tuff), 36.259 ± 0.016 Ma (Achenback Park tuff), and 36.215 ± 0.016 Ma (Squaw Mountain tuff). An alkali feldspar granite, which is chemically similar to the erupted tuffs, yielded a synchronous weighted mean [superscript 206]Pb/[superscript 238]U date of 36.259 ± 0.021 Ma. Weighted mean [superscript 206]Pb/[superscript 238]U dates from the larger volume syenitic phase of the underlying Organ Needle pluton range from 36.130 ± 0.031 to 36.071 ± 0.012 Ma, and the youngest sample is 144 ± 20 to 188 ± 20 ka younger than the Squaw Mountain and Achenback Park tuffs, respectively. Younger plutonism in the batholith continued through at least 34.051 ± 0.029 Ma. We propose that the Achenback Park tuff, Squaw Mountain tuff, alkali feldspar granite and Organ Needle pluton formed from a single, long-lived magma chamber/mush zone. Early silicic magmas generated by partial melting of the lower crust rose to form an epizonal magma chamber. Underplating of the resulting mush zone led to partial melting and generation of a high-silica alkali feldspar granite cap, which erupted to form the tuffs. The deeper parts of the chamber underwent continued recharge and crystallization for 144 ± 20 ka after the final eruption. Calculated magmatic fluxes for the Organ Needle pluton range from 0.0006 to 0.0030 km3/year, in agreement with estimates from other well-studied plutons. The petrogenetic evolution proposed here may be common to many small-volume silicic volcanic systems

Efficacy of Anti-Inflammatory Therapy in a Model of Acute Seizures and in a Population of Pediatric Drug Resistant Epileptics

Targeting pro-inflammatory events to reduce seizures is gaining momentum. Experimentally, antagonism of inflammatory processes and of blood-brain barrier (BBB) damage has been demonstrated to be beneficial in reducing status epilepticus (SE). Clinically, a role of inflammation in the pathophysiology of drug resistant epilepsies is suspected. However, the use anti-inflammatory drug such as glucocorticosteroids (GCs) is limited to selected pediatric epileptic syndromes and spasms. Lack of animal data may be one of the reasons for the limited use of GCs in epilepsy. We evaluated the effect of the CG dexamethasone in reducing the onset and the severity of pilocarpine SE in rats. We assessed BBB integrity by measuring serum S100β and Evans Blue brain extravasation. Electrophysiological monitoring and hematologic measurements (WBCs and IL-1β) were performed. We reviewed the effect of add on dexamethasone treatment on a population of pediatric patients affected by drug resistant epilepsy. We excluded subjects affected by West, Landau-Kleffner or Lennox-Gastaut syndromes and Rasmussen encephalitis, known to respond to GCs or adrenocorticotropic hormone (ACTH). The effect of two additional GCs, methylprednisolone and hydrocortisone, was also reviewed in this population. When dexamethasone treatment preceded exposure to the convulsive agent pilocarpine, the number of rats developing status epilepticus (SE) was reduced. When SE developed, the time-to-onset was significantly delayed compared to pilocarpine alone and mortality associated with pilocarpine-SE was abolished. Dexamethasone significantly protected the BBB from damage. The clinical study included pediatric drug resistant epileptic subjects receiving add on GC treatments. Decreased seizure frequency (≥50%) or interruption of status epilepticus was observed in the majority of the subjects, regardless of the underlying pathology. Our experimental results point to a seizure-reducing effect of dexamethasone. The mechanism encompasses improvement of BBB integrity. Our results also suggest that add on GCs could be of efficacy in controlling pediatric drug resistant seizures