Genetic analysis of GRIA2 and GRIA4 genes in migraine

Background Migraine is a brain disorder affecting ∼12% of the Caucasian population. Genes involved in neurological, vascular, and hormonal pathways have all been implicated in predisposing individuals to developing migraine. The migraineur presents with disabling head pain and varying symptoms of nausea, emesis, photophobia, phonophobia, and occasionally visual sensory disturbances. Biochemical and genetic studies have demonstrated dysfunction of neurotransmitters: serotonin, dopamine, and glutamate in migraine susceptibility. Glutamate mediates the transmission of excitatory signals in the mammalian central nervous system that affect normal brain function including cognition, memory and learning. The aim of this study was to investigate polymorphisms in the GRIA2 and GRIA4 genes, which encode subunits of the ionotropic AMPA receptor for association in an Australian Caucasian population. Methods Genotypes for each polymorphism were determined using high resolution melt analysis and the RFLP method. Results Statistical analysis showed no association between migraine and the GRIA2 and GRIA4 polymorphisms investigated. Conclusions Although the results of this study showed no significant association between the tested GRIA gene variants and migraine in our Australian Caucasian population further investigation of other components of the glutamatergic system may help to elucidate if there is a relationship between glutamatergic dysfunction and migraine.

Use of the biolistic particle delivery system to transform fungal genomes

Biolistic delivery of transforming DNA into fungal genomes, especially when performed on uninucleate haploid conidia, has proven successful in bypassing the time-consuming repetitive purification of protoplasts used for the widely applied polyethylene glycol-mediated method. Biolistic transformation is also relatively quick compared to other available methods and provides a high percentage of stable transformants.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

A new Salmonella typhimurium NM5004 strain expressing rat glutathione S-transferase 5-5 : use in detection of genotoxicity of dihaloalkanes using an SOS/umu test system

The Escherichia coli mu operon was subcloned into a pKK233-2 vector containing rat glutathione S-transferase (GST) 5-5 cDNA and the plasmid thus obtained was introduced into Salmonella typhimurium TA1535. The newly developed strain S.typhimurium NM5004, was found to have 52-fold greater GST activity than the original umu strain S.typhimurium TA1535/pSK1002. We compared sensitivities of these two tester strains, NM5004 and TA1535/ pSK1002, for induction of umuC gene expression with several dihaloalkanes which are activated or inactivated by GST 5-5 activity. The induction of umuC gene expression by these chemicals was monitored by measuring the cellular P-galactosidase activity produced by umuC'lacZ fusion gene in these two tester strains. Ethylene dibromide, 1-bromo-2-chloroethane, 1,2-dichloroethane, and methylene dichloride induced umuC gene expression more strongly in the NM5004 strain than the original strain, 4-Nitroquinoline 1-oxide and N-methyl-N'-nitro-N-nitrosoguanidine were found to induce umuC gene expression to similar extents in both strains. In the case of 1-nitropyrene and 2-nitrofluorene, however, NM5004 strain showed weaker umuC gene expression responses than the original TA1535/ pSK1002 strain, 1,2-Epoxy-3-(4'-nitrophenoxy)propane, a known substrate for GST 5-5, was found to inhibit umuC induction caused by 1-bromo-2-chloroethane. These results indicate that this new tester NM5004 strain expressing a mammalian GST theta class enzyme may be useful for studies of environmental chemicals proposed to be activated or inactivated by GST activity.

Markers of genetic susceptibility in human environmental hygiene and toxicology : the role of selected CYP, NAT and GST genes

Inherited genetic traits co-determine the susceptibility of an individual to a toxic chemical. Special emphasis has been put on individual responses to environmental and industrial carcinogens, but other chronic diseases are of increasing interest. Polymorphisms of relevant xenobiotic metabolising enzymes may be used as toxicological susceptibility markers. A growing number of genes encoding enzymes involved in biotransformation of toxicants and in cellular defence against toxicant-induced damage to the cells has been identified and cloned, leading to increased knowledge of allelic variants of genes and genetic defects that may result in a differential susceptibility toward environmental toxicants. "Low penetrating" polymorphisms in metabolism genes tend to be much more common in the population than allelic variants of "high penetrating" cancer genes, and are therefore of considerable importance from a public health point of view. Positive associations between cancer and CYP1A1 alleles, in particular the *2C I462V allele, were found for tissues following the aerodigestive tract. Again, in most cases, the effect of the variant CYP1A1 allele becomes apparent or clearer in connection with the GSTM1 null allele. The CYP1B1 codon 432 polymorphism (CYP1B1*3) has been identified as a susceptibility factor in smoking-related head-and-neck squameous cell cancer. The impact of this polymorphic variant of CYP1B1 on cancer risk was also reflected by an association with the frequency of somatic mutations of the p53 gene. Combined genotype analysis of CYP1B1 and the glutathione transferases GSTM1 or GSTT1 has also pointed to interactive effects. Of particular interest for the industrial and environmental field is the isozyme CYP2E1. Several genotypes of this isozyme have been characterised which seem to be associated with different levels of expression of enzyme activity. The acetylator status for NAT2 can be determined by genotyping or by phenotyping. In the pathogenesis of human bladder cancer due to occupational exposure to "classical" aromatic amines (benzidine, 4-aminodiphenyl, 1-naphthylamine) acetylation by NAT2 is regarded as a detoxication step. Interestingly, the underlying European findings of a higher susceptibility of slow acetylators towards aromatic amines are in contrast to findings in Chinese workers occupationally exposed to aromatic amines which points to different mechanisms of susceptibility between European and Chinese populations. Regarding human bladder cancer, the hypothesis has been put forward that genetic polymorphism of GSTM1 might be linked with the occurrence of this tumour type. This supports the hypothesis that exposure to PAH might causally be involved in urothelial cancers. The human polymorphic GST catalysing conjugation of halomethanes, dihalomethanes, ethylene oxide and a number of other industrial compounds could be characterised as a class theta enzyme (GSTT1) by means of molecular biology. "Conjugator" and "non-conjugator" phenotypes are coincident with the presence and absence of the GSTT1 gene. There are wide variations in the frequencies of GSTT1 deletion (GSTT1 *0/0) among different ethnicities. Human phenotyping is facilitated by the GST activity towards methyl bromide or ethylene oxide in erythrocytes which is representative of the metabolic GSTT1 competence of the entire organism. Inter-individual variations in xenobiotic metabolism capacities may be due to polymorphisms of the genes coding for the enzymes themselves or of the genes coding for the receptors or transcription factors which regulate the expression of the enzymes. Also, polymorphisms in several regions of genes may cause altered ligand affinity, transactivation activity or expression levels of the receptor subsequently influencing the expression of the downstream target genes. Studies of individual susceptibility to toxicants and gene-environment interaction are now emerging as an important component of molecular epidemiology.

Genetic susceptibility to environmental toxicants : the interface between human and experimental studies in the development of new toxicological concepts

The growing knowledge of the genetic polymorphisms of enzymes metabolising xenobiotics in humans and their connections with individual susceptibility towards toxicants has created new and important interfaces between human epidemiology and experimental toxicology. The results of molecular epidemiological studies may provide new hypotheses and concepts, which call for experimental verification, and experimental concepts may obtain further proof by molecular epidemiological studies. If applied diligently, these possibilities may be combined to lead to new strategies of human-oriented toxicological research. This overview will present some outstanding examples for such strategies taken from the practically very important field of occupational toxicology. The main focus is placed on the effects of enzyme polymorphisms of the xenobiotic metabolism in association with the induction of bladder cancer and renal cell cancer after exposure to occupational chemicals. Also, smoking and induction of head and neck squamous cell cancer are considered.

Hardware design and implementation of a MAVLink interface for an FPGA-based autonomous UAV flight control system

This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.

Efficiency of parallelisation of genetic algorithms in the data analysis context

Most real-life data analysis problems are difficult to solve using exact methods, due to the size of the datasets and the nature of the underlying mechanisms of the system under investigation. As datasets grow even larger, finding the balance between the quality of the approximation and the computing time of the heuristic becomes non-trivial. One solution is to consider parallel methods, and to use the increased computational power to perform a deeper exploration of the solution space in a similar time. It is, however, difficult to estimate a priori whether parallelisation will provide the expected improvement. In this paper we consider a well-known method, genetic algorithms, and evaluate on two distinct problem types the behaviour of the classic and parallel implementations.

Genetic risk score analysis indicates migraine with and without comorbid depression are genetically different disorders

Migraine and major depressive disorder (MDD) are comorbid, moderately heritable and to some extent influenced by the same genes. In a previous paper, we suggested the possibility of causality (one trait causing the other) underlying this comorbidity. We present a new application of polygenic (genetic risk) score analysis to investigate the mechanisms underlying the genetic overlap of migraine and MDD. Genetic risk scores were constructed based on data from two discovery samples in which genome-wide association analyses (GWA) were performed for migraine and MDD, respectively. The Australian Twin Migraine GWA study (N = 6,350) included 2,825 migraine cases and 3,525 controls, 805 of whom met the diagnostic criteria for MDD. The RADIANT GWA study (N = 3,230) included 1,636 MDD cases and 1,594 controls. Genetic risk scores for migraine and for MDD were used to predict pure and comorbid forms of migraine and MDD in an independent Dutch target sample (NTR-NESDA, N = 2,966), which included 1,476 MDD cases and 1,058 migraine cases (723 of these individuals had both disorders concurrently). The observed patterns of prediction suggest that the 'pure' forms of migraine and MDD are genetically distinct disorders. The subgroup of individuals with comorbid MDD and migraine were genetically most similar to MDD patients. These results indicate that in at least a subset of migraine patients with MDD, migraine may be a symptom or consequence of MDD. © 2013 Springer-Verlag Berlin Heidelberg.

Structural identification of a laboratory-based steel through truss cantilevered bridge with suspended span using a layered genetic algorithm with patternsearch step (GAPS)

Structural identification (St-Id) can be considered as the process of updating a finite element (FE) model of a structural system to match the measured response of the structure. This paper presents the St-Id of a laboratory-based steel through-truss cantilevered bridge with suspended span. There are a total of 600 degrees of freedom (DOFs) in the superstructure plus additional DOFs in the substructure. The St-Id of the bridge model used the modal parameters from a preliminary modal test in the objective function of a global optimisation technique using a layered genetic algorithm with patternsearch step (GAPS). Each layer of the St-Id process involved grouping of the structural parameters into a number of updating parameters and running parallel optimisations. The number of updating parameters was increased at each layer of the process. In order to accelerate the optimisation and ensure improved diversity within the population, a patternsearch step was applied to the fittest individuals at the end of each generation of the GA. The GAPS process was able to replicate the mode shapes for the first two lateral sway modes and the first vertical bending mode to a high degree of accuracy and, to a lesser degree, the mode shape of the first lateral bending mode. The mode shape and frequency of the torsional mode did not match very well. The frequencies of the first lateral bending mode, the first longitudinal mode and the first vertical mode matched very well. The frequency of the first sway mode was lower and that of the second sway mode was higher than the true values, indicating a possible problem with the FE model. Improvements to the model and the St-Id process will be presented at the upcoming conference and compared to the results presented in this paper. These improvements will include the use of multiple FE models in a multi-layered, multi-solution, GAPS St-Id approach.

Quantitative genetic modeling of lateral ventricular shape and volume using multi-atlas fluid image alignment in twins

Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

Mapping genetic influences on ventricular structure in twins

Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.

Phylogeographical relationships of Sicilian brown trout and the effects of genetic introgression on morphospace occupation

Genetic introgression of aquaculture stocks in local forms is well documented in many fish species but their evolutionary consequences for the local populations have not been thoroughly explored. Due to its wide geographical range, the existence of many locally adapted forms and the frequent occurrence of introgression of aquaculture stocks in local forms, brown trout represents the ideal system to study the effects of such introgressions. Here, we focus on a group of rivers and streams in Sicily (Italy), and, by using molecular tools, we show that autochthonous populations are probably derived from the Southern Atlantic clade, which is present in the Iberian peninsula and North Africa. Three out of the four studied rivers reveal signs of genetic introgression of domestic stocks. Finally, by using advanced geometric morphometric analyses, we show that genetic introgression produces a higher degree of morphological variability relative to that observed in non-introgressed populations.

Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist: A Mendelian randomisation analysis

Background To investigate potential cardiovascular and other effects of long-term pharmacological interleukin 1 (IL-1) inhibition, we studied genetic variants that produce inhibition of IL-1, a master regulator of inflammation. Methods We created a genetic score combining the effects of alleles of two common variants (rs6743376 and rs1542176) that are located upstream of IL1RN, the gene encoding the IL-1 receptor antagonist (IL-1Ra; an endogenous inhibitor of both IL-1α and IL-1β); both alleles increase soluble IL-1Ra protein concentration. We compared effects on inflammation biomarkers of this genetic score with those of anakinra, the recombinant form of IL-1Ra, which has previously been studied in randomised trials of rheumatoid arthritis and other inflammatory disorders. In primary analyses, we investigated the score in relation to rheumatoid arthritis and four cardiometabolic diseases (type 2 diabetes, coronary heart disease, ischaemic stroke, and abdominal aortic aneurysm; 453 411 total participants). In exploratory analyses, we studied the relation of the score to many disease traits and to 24 other disorders of proposed relevance to IL-1 signalling (746 171 total participants). Findings For each IL1RN minor allele inherited, serum concentrations of IL-1Ra increased by 0·22 SD (95% CI 0·18–0·25; 12·5%; p=9·3 × 10−33), concentrations of interleukin 6 decreased by 0·02 SD (−0·04 to −0·01; −1·7%; p=3·5 × 10−3), and concentrations of C-reactive protein decreased by 0·03 SD (−0·04 to −0·02; −3·4%; p=7·7 × 10−14). We noted the effects of the genetic score on these inflammation biomarkers to be directionally concordant with those of anakinra. The allele count of the genetic score had roughly log-linear, dose-dependent associations with both IL-1Ra concentration and risk of coronary heart disease. For people who carried four IL-1Ra-raising alleles, the odds ratio for coronary heart disease was 1·15 (1·08–1·22; p=1·8 × 10−6) compared with people who carried no IL-1Ra-raising alleles; the per-allele odds ratio for coronary heart disease was 1·03 (1·02–1·04; p=3·9 × 10−10). Per-allele odds ratios were 0·97 (0·95–0·99; p=9·9 × 10−4) for rheumatoid arthritis, 0·99 (0·97–1·01; p=0·47) for type 2 diabetes, 1·00 (0·98–1·02; p=0·92) for ischaemic stroke, and 1·08 (1·04–1·12; p=1·8 × 10−5) for abdominal aortic aneurysm. In exploratory analyses, we observed per-allele increases in concentrations of proatherogenic lipids, including LDL-cholesterol, but no clear evidence of association for blood pressure, glycaemic traits, or any of the 24 other disorders studied. Modelling suggested that the observed increase in LDL-cholesterol could account for about a third of the association observed between the genetic score and increased coronary risk. Interpretation Human genetic data suggest that long-term dual IL-1α/β inhibition could increase cardiovascular risk and, conversely, reduce the risk of development of rheumatoid arthritis. The cardiovascular risk might, in part, be mediated through an increase in proatherogenic lipid concentrations. Funding UK Medical Research Council, British Heart Foundation, UK National Institute for Health Research, National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council, and European Commission Framework Programme 7.

Genetic associations and functional characterization of M1 aminopeptidases and immune-mediated diseases

Endosplasmic reticulum aminopeptidase 1 (ERAP1), endoplasmic reticulum aminopeptidase 2 (ERAP2) and puromycin-sensitive aminopeptidase (NPEPPS) are key zinc metallopeptidases that belong to the oxytocinase subfamily of M1 aminopeptidase family. NPEPPS catalyzes the processing of proteosome-derived peptide repertoire followed by trimming of antigenic peptides by ERAP1 and ERAP2 for presentation on major histocompatibility complex (MHC) Class I molecules. A series of genome-wide association studies have demonstrated associations of these aminopeptidases with a range of immune-mediated diseases such as ankylosing spondylitis, psoriasis, Behçet's disease, inflammatory bowel disease and type I diabetes, and significantly, genetic interaction between some aminopeptidases and HLA Class I loci with which these diseases are strongly associated. In this review, we highlight the current state of understanding of the genetic associations of this class of genes, their functional role in disease, and potential as therapeutic targets.