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Force fields form the basis for classical molecular simulations, and their accuracy is crucial for the quality of, for instance, protein-ligand binding simulations in drug discovery. The huge diversity of small-molecule chemistry makes it a challenge to build and parameterize a suitable force field. The Open Force Field Initiative is a combined industry and academic consortium developing a state-of-the-art small-molecule force field. In this report, industry members of the consortium worked together to objectively evaluate the performance of the force fields (referred to here as OpenFF) produced by the initiative on a combined public and proprietary dataset of 19,653 relevant molecules selected from their internal research and compound collections. This evaluation was important because it was completely blind; at most partners, none of the molecules or data were used in force field development or testing prior to this work. We compare the Open Force Field "Sage" version 2.0.0 and "Parsley" version 1.3.0 with GAFF-2.11-AM1BCC, OPLS4, and SMIRNOFF99Frosst. We analyzed force-field-optimized geometries and conformer energies compared to reference quantum mechanical data. We show that OPLS4 performs best, and the latest Open Force Field release shows a clear improvement compared to its predecessors. The performance of established force fields such as GAFF-2.11 was generally worse. While OpenFF researchers were involved in building the benchmarking infrastructure used in this work, benchmarking was done entirely in-house within industrial organizations and the resulting assessment is reported here. This work assesses the force field performance using separate benchmarking steps, external datasets, and involving external research groups. This effort may also be unique in terms of the number of different industrial partners involved, with 10 different companies participating in the benchmark efforts.

Force fields form the basis for classical molecular simulations, and their accuracy is crucial for the quality of, for instance, protein-ligand binding simulations in drug discovery. The huge diversity of small-molecule chemistry makes it a challenge to build and parameterize a suitable force field. The Open Force Field Initiative is a combined industry and academic consortium developing a state-of-the-art small-molecule force field. In this report, industry members of the consortium worked together to objectively evaluate the performance of the force fields (referred to here as OpenFF) produced by the initiative on a combined public and proprietary dataset of 19,653 relevant molecules selected from their internal research and compound collections. This evaluation was important because it was completely blind; at most partners, none of the molecules or data were used in force field development or testing prior to this work. We compare the Open Force Field "Sage" version 2.0.0 and "Parsley" version 1.3.0 with GAFF-2.11-AM1BCC, OPLS4, and SMIRNOFF99Frosst. We analyzed force-field-optimized geometries and conformer energies compared to reference quantum mechanical data. We show that OPLS4 performs best, and the latest Open Force Field release shows a clear improvement compared to its predecessors. The performance of established force fields such as GAFF-2.11 was generally worse. While OpenFF researchers were involved in building the benchmarking infrastructure used in this work, benchmarking was done entirely in-house within industrial organizations and the resulting assessment is reported here. This work assesses the force field performance using separate benchmarking steps, external datasets, and involving external research groups. This effort may also be unique in terms of the number of different industrial partners involved, with 10 different companies participating in the benchmark efforts.

Introduction Familial hypercholesterolaemia (FH) is a common, heritable and preventable cause of premature coronary artery disease, with significant potential for positive impact on public health and healthcare savings. New clinical practice recommendations are presented in an abridged guidance to assist practitioners in enhancing the care of all patients with FH. Main recommendations Core recommendations are made on the detection, diagnosis, assessment and management of adults, children and adolescents with FH. There is a key role for general practitioners (GPs) working in collaboration with specialists with expertise in lipidology. Advice is given on genetic and cholesterol testing and risk notification of biological relatives undergoing cascade testing for FH; all healthcare professionals should develop skills in genomic medicine. Management is under-pinned by the precepts of risk stratification, adherence to healthy lifestyles, treatment of non-cholesterol risk factors, and appropriate use of low-density lipoprotein (LDL)-cholesterol lowering therapies, including statins, ezetimibe and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors. Recommendations on service design are provided in the full guidance. Potential impact on care of FH These recommendations need to be utilised using judicious clinical judgement and shared decision making with patients and families. Models of care need to be adapted to both local and regional needs and resources. In Australia new government funded schemes for genetic testing and use of PCSK9 inhibitors, as well as the National Health Genomics Policy Framework, will enable adoption of these recommendations. A broad implementation science strategy is, however, required to ensure that the guidance translates into benefit for all families with FH.

Familial hypercholesterolaemia (FH) is a dominant and highly penetrant monogenic disorder present from birth that markedly elevates plasma low-density lipoprotein (LDL)-cholesterol concentration and, if untreated, leads to premature atherosclerosis and coronary artery disease (CAD). There are approximately 100,000 people with FH in Australia. However, an overwhelming majority of those affected remain undetected and inadequately treated, consistent with FH being a leading challenge for public health genomics. To further address the unmet need, we provide an updated guidance, presented as a series of systematically collated recommendations, on the care of patients and families with FH. These recommendations have been informed by an exponential growth in published works and new evidence over the last 5 years and are compatible with a contemporary global call to action on FH. Recommendations are given on the detection, diagnosis, assessment and management of FH in adults and children. Recommendations are also made on genetic testing and risk notification of biological relatives who should undergo cascade testing for FH. Guidance on management is based on the concepts of risk re-stratification, adherence to heart healthy lifestyles, treatment of non-cholesterol risk factors, and safe and appropriate use of LDL-cholesterol lowering therapies, including statins, ezetimibe, proprotein convertase subtilisin/kexin type 9 inhibitors and lipoprotein apheresis. Broad recommendations are also provided for the organisation and development of health care services. Recommendations on best practice need to be underpinned by good clinical judgment and shared decision making with patients and families. Models of care for FH need to be adapted to local and regional health care needs and available resources. A comprehensive and realistic implementation strategy, informed by further research, including assessments of cost-benefit, will be required to ensure that this new guidance benefits

Importance: Familial hypercholesterolemia (FH) is an underdiagnosed and undertreated genetic disorder that leads to premature morbidity and mortality due to atherosclerotic cardiovascular disease. Familial hypercholesterolemia affects 1 in 200 to 250 people around the world of every race and ethnicity. The lack of general awareness of FH among the public and medical community has resulted in only 10% of the FH population being diagnosed and adequately treated. The World Health Organization recognized FH as a public health priority in 1998 during a consultation meeting in Geneva, Switzerland. The World Health Organization report highlighted 11 recommendations to address FH worldwide, from diagnosis and treatment to family screening and education. Research since the 1998 report has increased understanding and awareness of FH, particularly in specialty areas, such as cardiology and lipidology. However, in the past 20 years, there has been little progress in implementing the 11 recommendations to prevent premature atherosclerotic cardiovascular disease in an entire generation of families with FH. Observations: In 2018, the Familial Hypercholesterolemia Foundation and the World Heart Federation convened the international FH community to update the 11 recommendations. Two meetings were held: one at the 2018 FH Foundation Global Summit and the other during the 2018 World Congress of Cardiology and Cardiovascular Health. Each meeting served as a platform for the FH community to examine the original recommendations, assess the gaps, and provide commentary on the revised recommendations. The Global Call to Action on Familial Hypercholesterolemia thus represents individuals with FH, advocacy leaders, scientific experts, policy makers, and the original authors of the 1998 World Health Organization report. Attendees from 40 countries brought perspectives on FH from low-, middle-, and high-income regions. Tables listing country-specific government support for FH care, existing

Few people would dispute the fact that there is a bewildering array of books available on the business of eating, fitness and nutrition, many of them, unfortunately, with (hidden) vested interests in the food industry and singular theories. But every now

A key feature of major depressive disorder (MDD) is anhedonia, which is a predictor of response to antidepressant treatment. In order to shed light on its genetic underpinnings, we conducted a genome-wide association study (GWAS) followed by investigation of biological pathway enrichment using an anhedonia dimension for 759 patients with MDD in the GENDEP study. The GWAS identified 18 SNPs associated at genome-wide significance with the top one being an intronic SNP (rs9392549) in PRPF4B (pre-mRNA processing factor 4B) located on chromosome 6 (P = 2.07 × 10−9) while gene-set enrichment analysis returned one gene ontology term, axon cargo transport (GO: 0008088) with a nominally significant P value (1.15 × 10−5). Furthermore, our exploratory analysis yielded some interesting, albeit not statistically significant genetic correlation with Parkinson’s Disease and nucleus accumbens gray matter. In addition, polygenic risk scores (PRSs) generated from our association analysis were found to be able to predict treatment efficacy of the antidepressants in this study. In conclusion, we found some markers significantly associated with anhedonia, and some suggestive findings of related pathways and biological functions, which could be further investigated in other studies., SCOPUS: ar.j, info:eu-repo/semantics/published

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects. CYP2C19 metabolic phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was assessed by standardized percentage symptom improvement and by remission. Side effect data were available at weeks 2–4, 6 and 9 in three samples. A fixed-effects meta-analysis was performed using EM as the reference group. Analysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD = 0.43, CI = 0.19–0.66) and higher remission rates (OR = 1.55, CI = 1.23–1.96) compared to EMs. At weeks 2–4, PMs showed higher risk of gastro-intestinal (OR = 1.26, CI = 1.08–1.47), neurological (OR = 1.28, CI = 1.07–1.53) and sexual side effects (OR = 1.52, CI = 1.23–1.87; week 6 values were similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups. CYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs being relatively rare among Caucasians (∼2%)., SCOPUS: ar.j, info:eu-repo/semantics/published

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STARD) studies was performed at the single-nucleotide polymorphism (SNP), gene and pathway levels. Coverage of genetic variants was increased compared with previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. Significant findings were investigated in NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) for replication. A total of 7062 950 SNPs were analyzed in GENDEP (n = 738) and STARD (n = 1409). rs116692768 (P = 1.80e ?08, ITGA9 (integrin ?9)) and rs76191705 (P = 2.59e ?08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At the gene level, no consistent effect was found. At the pathway level, the Gene Ontology (GO) terms GO: 0005694 (chromosome) and GO: 0044427 (chromosomal part) were associated with improvement (corrected P = 0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (P = 0.047), whereas rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, replication was partial. Further studies may help in cl, SCOPUS: ar.j, info:eu-repo/semantics/published

Familial Hypercholesterolemia (FH) is the most common and serious monogenic disorder of lipoprotein metabolism that leads to premature coronary heart disease. There are over 65,000 people estimated to have FH in Australia, but many remain undiagnosed. Patients with FH are often under-treated, but with early detection, cascade family testing and adequate treatment, patient outcomes can improve. Patient registries are key tools for providing new information on FH and enhancing care worldwide. The development and design of the FH Australasia Network Registry is a crucial component in the comprehensive model of care for FH, which aims to provide a standardized, high-quality and cost-effective system of care that is likely to have the highest impact on patient outcomes. Informed by stakeholder engagement, the FH Australasia Network Registry was collaboratively developed by government, patient and clinical networks and research groups. The open-source, web-based Rare Disease Registry Framework was the architecture chosen for this registry owing to its open-source standards, modular design, interoperability, scalability and security features; all these are key components required to meet the ever changing clinical demands across regions. This paper provides a high level blueprint for other countries and jurisdictions to help inform and map out the critical features of an FH registry to meet their particular health system needs.

Cet article a pour but d’explorer la façon dont les concepts de l’engagement interculturel, (intercultural engagement) utilisés dans la traductologie littéraire des Caraïbes et dans l’éducation critique pour la citoyenneté mondiale, mettent en question les concepts sous-jacents dans le discours managérialiste de l’internationalisation prédominant actuellement dans les Caraïbes anglophones et dans d’autres systèmes d’enseignement supérieur. En s’appuyant sur l’œuvre d’Édouard Glissant, en particulier, on illustre le potentiel de la pensée caribéenne pour créer de précieuses manières d’interrelation qui reconnaissent elles-mêmes la nature intrinsèquement problématique des interactions interculturelles. La circulation de traductions littéraires entre les Caraïbes anglophones et Cuba s’évoquent comme un possible centre d’intérêt du développement pédagogique et de recherche autour des idées abordées., This paper explores ways in which frameworks of intercultural engagement used in Caribbean Literary Translation Studies and in Critical Global Citizenship Education contest those implied by the managerialist discourse of internationalization currently predominant in Anglophone Caribbean and other higher education systems. The work of Édouard Glissant, particularly, is used to exemplify the potential of Caribbean thought for supplying rich forms of inter-relation that acknowledge the inherently problematic character of intercultural interactions. Literary translation flows between the Anglophone Caribbean and Cuba are invoked as a possible site of pedagogical and research development around the ideas discussed.

Full Text, Thesis (PhD Doctorate), Doctor of Philosophy (PhD), School of Applied Psychology, Griffith Health, A relationship exists between mood and cardiac control systems. This relationship has been established through correlations between medical pathology, such as Coronary Heart Disease (CHD), and psychopathological changes in mood, such as Major Depressive Disorder (MDD). Euthymic mood and normal cardiac regulation, as well as the diseases MDD and CHD, are linked by numerous interrelated physiological pathways. These pathways form part of a physiological regulatory network in the body called the psycho-immune-neuroendocrine (PINE) network. PINE network homeostasis can be disrupted by stress, resulting in pathological changes, which give rise to MDD, CHD, or both diseases. Heart Rate Variability (HRV) is a physiological measure of cardiac function which reflects autonomic cardiac control, an important component of the PINE network. This body of work set out to test three hypotheses, the first being that psychometric measures of mood and HRV measures are related across a broad range of mood, from non-pathological to pathological depressed mood. The second hypothesis is that psychometric measures of mood and HRV measures remain related over time, even when an individual’s mood changes across time. The third hypothesis is that in people with CHD, HRV measures would still be related to mood, but HRV may be globally reduced compared to people without CHD. A longitudinal cohort study, the Heart and Mind Study, recruited 88 participants and followed them up over six months.

Hundreds of millions of people rely on forested water catchments for potable drinking water. However, rainfall subsequent to widespread wildfire can result in high concentrations of suspended sediment entering waterways, and eventually, water supply reservoirs. Calculation of the risk wildfire poses to water quality of supply reservoirs involves consideration of both probabilistic and deterministic processes which intersect at a wide range of scales and resolutions, in time and space. Two of the key requirements necessary to develop a suitable risk model are i) the generation of spatially distributed burn intensity data of future fires to inform subsequent erosion models, and ii) an improved understanding of the relationship between spatial scale and post fire hydro-geomorphic processes. This thesis addresses these two areas, to support the future development of a post fire hydro-geomorphic risk model. A probabilistic wildfire burn area simulation model is developed and presented which delivers the required spatially distributed burn intensity data, while also replicating the fire frequency and magnitude of the local fire regime. The model relies on historical fire records and the adaption of an existing fire behaviour simulator to produce the desired output data. These data can then parameterise deterministic hydrological and erosion process sub-models to determine local post fire water quality risk. Further development of the wildfire model will allow more accurate simulation of the local fire regime. The relationship between spatial scale and post fire hydro-geomorphic processes is poorly understood, which prevents further development of a post fire hydro-geomorphic risk model. This thesis includes an analysis conducted to improve understanding of wildfire effects on peak discharge at the large catchment scale. Pre and post wildfire rainfall and runoff data from six large catchments in Australia’s southeast upland forests were analysed to determine whether wildfi

The mechanisms by which antidepressants have their effects are not clear and the reasons for variability in treatment outcomes are also unknown. However, there is evidence from candidate gene research that indicates gene expression changes may be involved in antidepressant action. In this study, we examined antidepressant-induced alterations in gene expression on a transcriptome-wide scale, exploring associations with treatment response. Blood samples were taken from a subset of depressed patients from the GENDEP study (n=136) before and after eight weeks of treatment with either escitalopram or nortriptyline. Transcriptomic data were obtained from these samples using Illumina HumanHT-12 v4 Expression BeadChip microarrays. When analysing individual genes, we observed that changes in the expression of two genes (MMP28 and KXD1) were associated with better response to nortriptyline. Considering connectivity between genes, we identified modules of genes that were highly coexpressed. In the whole sample, changes in one of the ten identified coexpression modules showed significant correlation with treatment response (cor=0.27, p=0.0029). Using transcriptomic approaches, we have identified gene expression correlates of the therapeutic effects of antidepressants, highlighting possible molecular pathways involved in efficacious antidepressant treatment., SCOPUS: ar.j, info:eu-repo/semantics/published

Rationale: Cytochrome P450 enzymes are important in the metabolism of antidepressants. The highly polymorphic nature of these enzymes has been linked to variability in antidepressant metabolism rates, leading to hope regarding the use of P450 genotyping to guide treatment. However, evidence that P450 genotypic differences underlie the variation in treatment outcomes is inconclusive. Objectives: We explored the links between both P450 genotype and serum concentrations of antidepressant with antidepressant side effects, using data from the Genome-Based Therapeutic Drugs for Depression Project (GENDEP), which is a large (n = 868), pharmacogenetic study of depressed individuals treated with escitalopram or nortriptyline. Methods: Patients were genotyped for the enzymes CYP2C19 and CYP2D6, and serum concentrations of both antidepressant and primary metabolite were measured after 8 weeks of treatment. Side effects were assessed weekly. We investigated associations between P450 genotypes, serum concentrations of antidepressants and side effects, as well as the relationship between P450 genotype and study discontinuation. Results: P450 genotype did not predict total side effect burden (nortriptyline: n = 251, p = 0.5638, β = -0.133, standard error (SE) = 0.229; escitalopram: n = 340, p = 0.9627, β = -0.004, SE = 0.085), study discontinuation (nortriptyline n = 284, hazard ratio (HR) = 1.300, p = 0.174; escitalopram n = 376, HR = 0.870, p = 0.118) or specific side effects. Serum concentrations of antidepressant were only related to a minority of the specific side effects measured: dry mouth, dizziness and diarrhoea. Conclusions: In this sample where antidepressant dosage is titrated using clinical judgement, P450 genotypes do not explain differences between patients in side effects with antidepressants. Serum drug concentrations appear to only explain variability in the occurrence of a minority of specific side effects., SCOPUS: ar.j, info:eu-repo/semantics/published

Background Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability). Method For investigating familiality, we used 691 families with 2-5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software. Results Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity. Conclusions AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses., SCOPUS: ar.j, info:eu-repo/semantics/published

This thesis investigates both the release of energy in solar flares, and the acceleration and transport of particles in various astrophysical situations. While numerical simulations are central to this thesis, these are always motivated by analytical arguments. A review of flare energy release is given in Chapter 2, with results presented in Chapters 3 and 4. The main goal of the flare work is to investigate the effect of viscosity on energy release rates. Scaling arguments and exact solutions of the magnetohydrodynamic equations are used to interpret the results of two-dimensional numerical simulations of magnetic reconnection. The results support viscous energy dissipation accounting for a significant fraction of flare energy release. Chapter 5 contains an introduction to astrophysical particle acceleration, using the Fokker-Planck formulation. The theory introduced in this chapter is used to study electron transport in solar flare loops (Section 5.5). A key aspect of the analysis is the expression of the Fokker-Planck equation as a system of stochastic differential equations. A generalisation to the flare loop hard X-ray emission prediction of Conway et al. (1998) is obtained, giving a stronger dependence on density for dispersed initial distributions. Chapter 6 uses the methods of the previous chapter to study the acceleration of cosmic-rays at the heliospheric termination shock. The applicability of the focused acceleration mechanism of Schlickeiser and Shalchi (2008) is examined using numerical simulations, which are interpreted using analytical arguments based on averaging the stochastic equations. The results show significant limitations in assuming a near-isotropic distribution, a requirement for the focused acceleration mechanism. In addition, momentum diffusion provides a significant effect that cannot be neglected. The theory is extended to include focused deceleration and pure momentum diffusion.

Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve.

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.

It would be beneficial to find genetic predictors of antidepressant response to help personalise treatment of major depressive disorder (MDD). Rare copy number variants (CNVs) have been implicated in several psychiatric disorders, including MDD, but their role in antidepressant response has yet to be investigated. CNV data were available for 1565 individuals with MDD from the NEWMEDS (Novel Methods leading to New Medications in Depression and Schizophrenia) consortium with prospective data on treatment outcome with either a serotonergic or noradrenergic antidepressant. No association was seen between the presence of CNV (rare or common), the overall number of CNVs or genomic CNV 'burden' and antidepressant response. Specific CNVs were nominally associated with antidepressant response, including 15q13.3 duplications and exonic NRXN1 deletions. These were associated with poor response to antidepressants. Overall burden of CNVs is unlikely to contribute to personalising antidepressant treatment. Specific CNVs associated with antidepressant treatment require replication and further study to confirm their role in the therapeutic action of antidepressant. © 2014 Macmillan Publishers Limited All rights reserved., SCOPUS: ar.j, info:eu-repo/semantics/published

Aims: Antidepressant response varies between patients, possibly due to differences in the rate cytochrome P450 enzymes metabolise antidepressants into inactive compounds. Drug metabolism rates are influenced by common variants in the genes encoding these enzymes. However, it remains unclear whether treatment outcomes can be predicted by either CYP450 genotype or antidepressant serum concentration. Methods: In GENDEP (a pharmacogenetic study of depressed individuals treated with either escitalopram or nortriptyline), serum concentrations of antidepressants and their primary metabolite were measured after eight weeks treatment and variants in CYP2D6 and CYP2C19 were genotyped. Results: Amongst patients taking escitalopram (n=223), the genotype CYP2C19 was significantly associated with escitalopram serum concentrations and desmethylescitalopram:escitalopram ratio. For those taking nortriptyline (n=161), the CYP2D6 genotype was significantly associated with nortriptyline and 10-hydroxynortriptyline serum concentrations and 10-hydroxynortriptyline: nortriptyline ratio. CYP450 genotypes conferring greater enzyme activity were linked to lower drug serum concentrations and higher metabolite:drug ratios. Nonetheless, no significant association was found between either CYP450 genotype or antidepressant serum concentration and treatment response. Conclusions: While there is a significant relationship between the CYP450 genotype and serum concentrations of escitalopram and nortriptyline, the genotypes are not predictive of differences in treatment response for either drug. Furthermore, differences in antidepressant serum concentrations are not associated with variability in treatment response. © The Author(s) 2013., SCOPUS: ar.j, info:eu-repo/semantics/published

Objective: Indirect evidence suggests that common genetic variation contributes to individual differences in antidepressant efficacy among individuals with major depressive disorder, but previous studies may have been underpowered to detect these effects. Method: A meta-analysis was performed on data from three genome-wide pharma-cogenetic studies (the Genome-Based Therapeutic Drugs for Depression [GENDEP] project, the Munich Antidepressant Response Signature [MARS] project, and the Sequenced Treatment Alternatives to Relieve Depression [STAR*D] study), which included 2,256 individuals of Northern European descent with major depressive disorder, and antidepressant treatment outcomes were prospectively collected. After imputation, 1.2 million single-nucleotide polymorphisms were tested, capturing common variation for association with symptomatic improvement and remission after up to 12 weeks of antidepressant treatment. Results: No individual association met a genome-wide threshold for statistical significance in the primary analyses. A polygenic score derived from a meta-analysis of GENDEP and MARS participants accounted for up to approximately 1.2% of the variance in outcomes in STAR*D, suggesting a weakly concordant signal distributed over many polymorphisms. An analysis restricted to 1,354 individuals treated with citalopram (STAR*D) or escitalopram (GENDEP) identified an intergenic region on chromosome 5 associated with early improvement after 2 weeks of treatment. Conclusions: Despite increased statistical power accorded by meta-analysis, the authors identified no reliable predictors of antidepressant treatment outcome, although they did identify modest, direct evidence that common genetic variation contributes to individual differences in antidepressant response., SCOPUS: ar.j, info:eu-repo/semantics/published

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohns disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

Objectives. Co-morbidity between depression and anxiety disorders is common. In this study we define a quantitative measure of anxiety by summating four anxiety items from the SCAN interview in a large collection of major depression (MDD) cases to identify genes contributing to this complex phenotype. Methods. A total of 1522 MDD cases dichotomised according to those with at least one anxiety item scored (n = 1080) and those without anxiety (n = 442) were analysed, and also compared to 1588 healthy controls at a genome-wide level, to identify genes that may contribute to anxiety in MDD. Results. For the quantitative trait, suggestive evidence of association was detected for two SNPs, and for the dichotomous anxiety present/absent ratings for three SNPs at genome-wide level. In the genome-wide analysis of MDD cases with co-morbid anxiety and healthy controls, two SNPs attained P values of < 5 × 10-6. Analysing candidate genes, P values ≤ 0.0005 were found with three SNPs for the quantitative trait and three SNPs for the dichotomous trait. Conclusions. This study provides an initial genome-wide assessment of possible genetic contribution to anxiety in MDD. Although suggestive evidence of association was found for several SNPs, our findings suggest that there are no common variants strongly associated with anxious depression. © 2013 Informa Healthcare., SCOPUS: ar.j, info:eu-repo/semantics/published

Suicidal thoughts during antidepressant treatment have been the focus of several candidate gene association studies. The aim of the present genome-wide association study was to identify additional genetic variants involved in increasing suicidal ideation during escitalopram and nortriptyline treatment. A total of 706 adult participants of European ancestry, treated for major depression with escitalopram or nortriptyline over 12 weeks in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study were genotyped with Illumina Human 610-Quad Beadchips (Illumina, San Diego, CA, USA). A total of 244 subjects experienced an increase in suicidal ideation during follow-up. The genetic marker most significantly associated with increasing suicidality (8.28 × 10 7) was a single-nucleotide polymorphism (SNP; rs11143230) located 30 kb downstream of a gene encoding guanine deaminase (GDA) on chromosome 9q21.13. Two suggestive drug-specific associations within KCNIP4 (Kv channel-interacting protein 4; chromosome 4p15.31) and near ELP3 (elongation protein 3 homolog; chromosome 8p21.1) were found in subjects treated with escitalopram. Suggestive drug by gene interactions for two SNPs near structural variants on chromosome 4q12, one SNP in the apolipoprotein O (APOO) gene on chromosome Xp22.11 and one on chromosome 11q24.3 were found. The most significant association within a set of 33 candidate genes was in the neurotrophic tyrosine kinase receptor type 2 (NTRK2) gene. Finally, we also found trend for an association within genes previously associated with psychiatric phenotypes indirectly linked to suicidal behavior, that is, GRIP1, NXPH1 and ANK3. The results suggest novel pathways involved in increasing suicidal ideation during antidepressant treatment and should help to target treatment to reduce the risk of this dramatic adverse event. Limited power precludes definitive conclusions and replication in larger sample is warranted. © 2012 Macmillan Publishers Limited. All right, SCOPUS: ar.j, info:eu-repo/semantics/published

Genome-wide studies in major depression have identified few replicated associations, potentially due to heterogeneity within the disorder. Several studies have suggested that age at onset (AAO) can distinguish sub-types of depression with specific heritable components. This paper investigates the role of AAO in the genetic susceptibility for depression using genome-wide association data on 2,746 cases and 1,594 screened controls from the RADIANT studies, with replication performed in 1,471 cases and 1,403 controls from two Munich studies. Three methods were used to analyze AAO: First a time-to-event analysis with controls censored, secondly comparing controls to case-subsets defined using AAO cut-offs, and lastly analyzing AAO as a quantitative trait. In the time-to-event analysis three SNPs reached suggestive significance (P<5E-06), overlapping with the original case-control analysis of this study. In a case-control analysis using AAO thresholds, SNPs in 10 genomic regions showed suggestive association though again none reached genome-wide significance. Lastly, case-only analysis of AAO as a quantitative trait resulted in 5 SNPs reaching suggestive significance. Sex specific analysis was performed as a secondary analysis, yielding one SNP reaching genome-wide significance in early-onset males. No SNPs achieved significance in the replication study after correction for multiple testing. Analysis of AAO as a quantitative trait did suggest that, across all SNPs, common genetic variants explained a large proportion of the variance (51%, P=0.04). This study provides the first focussed analysis of the genetic contribution to AAO in depression, and establishes a statistical framework that can be applied to a quantitative trait underlying any disorder. © 2012 Wiley Periodicals, Inc., SCOPUS: ar.j, info:eu-repo/semantics/published

In vitro work shows CYP2C19 and CYP2D6 contribute to the metabolism of escitalopram to its primary metabolite, N-desmethylescitalopram. We report the effect of CYP2C19 and CYP2D6 genotypes on steady state morning concentrations of escitalopram and N-desmethylescitalopram and the ratio of this metabolite to the parent drug in 196 adult patients with depression in GENDEP, a clinical pharmacogenomic trial. Subjects who had one CYP2D6 allele associated with intermediate metabolizer phenotype and one associated with poor metabolizer (i.e. IM/PM genotypic category) had a higher mean logarithm escitalopram concentration than CYP2D6 extensive metabolizers (EMs) (p=0.004). Older age was also associated with higher concentrations of escitalopram. Covarying for CYP2D6 and age, we found those homozygous for the CYP2C19*17 allele associated with ultrarapid metabolizer (UM) phenotype had a significantly lower mean escitalopram concentration (2-fold, p=0.0001) and a higher mean metabolic ratio (p=0.0003) than EMs, while those homozygous for alleles conferring the PM phenotype had a higher mean escitalopram concentration than EMs (1.55-fold, p=0.008). There was a significant overall association between CYP2C19 genotypic category and escitalopram concentration (p=0.0003; p=0.0012 Bonferroni corrected). In conclusion, we have demonstrated an association between CYP2C19 genotype, including the CYP2C19*17 allele, and steady state escitalopram concentration. © 2012 British Association for Psychopharmacology., SCOPUS: ar.j, info:eu-repo/semantics/published

Background: It has been suggested that outcomes of antidepressant treatment for major depressive disorder could be significantly improved if treatment choice is informed by genetic data. This study aims to test the hypothesis that common genetic variants can predict response to antidepressants in a clinically meaningful way. Methods and Findings: The NEWMEDS consortium, an academia-industry partnership, assembled a database of over 2,000 European-ancestry individuals with major depressive disorder, prospectively measured treatment outcomes with serotonin reuptake inhibiting or noradrenaline reuptake inhibiting antidepressants and available genetic samples from five studies (three randomized controlled trials, one part-randomized controlled trial, and one treatment cohort study). After quality control, a dataset of 1,790 individuals with high-quality genome-wide genotyping provided adequate power to test the hypotheses that antidepressant response or a clinically significant differential response to the two classes of antidepressants could be predicted from a single common genetic polymorphism. None of the more than half million genetic markers significantly predicted response to antidepressants overall, serotonin reuptake inhibitors, or noradrenaline reuptake inhibitors, or differential response to the two types of antidepressants (genome-wide significance p<5×10 -8). No biological pathways were significantly overrepresented in the results. No significant associations (genome-wide significance p<5×10 -8) were detected in a meta-analysis of NEWMEDS and another large sample (STAR*D), with 2,897 individuals in total. Polygenic scoring found no convergence among multiple associations in NEWMEDS and STAR*D. Conclusions: No single common genetic variant was associated with antidepressant response at a clinically relevant level in a European-ancestry cohort. Effects specific to particular antidepressant drugs could not be investigated in the current study. Please see later, SCOPUS: ar.j, info:eu-repo/semantics/published

There is substantial inter-individual variation in response and adverse reactions to antidepressants, and genetic variation may, in part, explain these differences. GNB3 encodes the β3 subunit of the G protein complex, which is involved in the downstream signalling cascade following monoamine receptor activation. A functional polymorphism in this gene (C825T) has been associated with response to antidepressants. Several lines of evidence suggest that GNB3 moderates improvement in the neurovegetative symptoms of depression (such as sleep and appetite) and related adverse reactions independently of change in core mood symptoms. We here report analysis of data from GENDEP, a part-randomized pharmacogenomic trial, on the outcome of 811 subjects with major depression undergoing treatment with either escitalopram or nortriptyline in which the C825T SNP and three further SNPs in GNB3 were genotyped. The TT genotype was significantly associated with a superior response to nortriptyline and these effects were specific to improvements in neurovegetative symptoms. In addition, the same genotype predicted fewer incidents of treatment-emergent insomnia and greater weight gain on the same drug. Our results are consistent with previous associations with GNB3 and emphasize the importance of signalling genes in antidepressant response. © The Author(s) 2011 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav., SCOPUS: ar.j, info:eu-repo/semantics/published

There is substantial inter-individual variation in response to antidepressants, and genetic variation may, in part, explain these differences. For example, there is evidence to suggest that variation in the serotonin transporter gene (SLC6A4) predicts response to selective serotonin reuptake inhibitors (SSRIs). Environmental factors such as the occurrence of stressful life events before treatment may also be important. One prior report suggests that both factors interact in predicting response to antidepressants. GENDEP, a prospective part-randomized pharmacogenomics trial, collected longitudinal data on the outcome of 811 patients with major depression undergoing treatment with either an SSRI (escitalopram) or a tricyclic antidepressant (nortriptyline). Life events experienced over 6 months preceding treatment were measured using a List of Threatening Experiences Questionnaire, and several polymorphisms in the serotonin transporter gene (SLC6A4) have been genotyped including the serotonin transporter-linked polymorphic region (5-HTTLPR). Stressful life events were shown to predict a significantly better response to escitalopram but had no effect on response to nortriptyline. Variation in the 5-HTTLPR and another polymorphism in the gene, STin4, significantly modified these effects. Gene-environment interactions including life events may therefore be important not only in the aetiology of depression, but also in predicting response to antidepressant medication. © 2011 Macmillan Publishers Limited. All rights reserved., SCOPUS: ar.j, info:eu-repo/semantics/published

Background Antidepressant drugs are used as first-line treatment in depression, but response has been shown to be highly heterogeneous, with drugs often failing to have the desired therapeutic effect. We report on an integrative analysis from the Genome-Based Therapeutic Drugs for Depression (GENDEP) study using gene expression from mice to inform prioritization in a human pharmacogenetic study. Methods The same two antidepressants were used in mice and humans: escitalopram (a serotonin reuptake inhibitor) and nortriptyline (a norepinephrine reuptake inhibitor). The animal study used four inbred strains of mice (129S1/SvlmJ, C57LB/6J, DBA/2J, and FVB/NJ). Hippocampus mRNA levels were measured in 144 animals using the Affymetrix MOE 430 v2 chip. Results Based on gene-expression analysis of strain-by-drug interactions, 17 genes differentially expressed with nortriptyline or escitalopram versus saline were prioritized in the human pharmacogenetic analysis. Single nucleotide polymorphisms tagging common sequence variation in human orthologs of these genes were tested for association with response to antidepressants in 706 participants of the GENDEP human pharmacogenetic study, treated with escitalopram or nortriptyline for 12 weeks, with available high-quality Illumina 610 quad array genotyping. Several polymorphisms in the protein phosphatase 1A gene (PPM1A) remained significantly associated with response to nortriptyline in humans after correction for multiple comparisons within the gene. PPM1A encodes a phosphatase involved in mitogen-activated protein kinase signaling and cell stress response. Conclusions Convergent evidence from mice and humans suggests a role of the PPM1A in response to noradrenergic but not serotonergic antidepressants. © 2011 Society of Biological Psychiatry., SCOPUS: ar.j, info:eu-repo/semantics/published

La literatura del Caribe anglófono se ha forjado una identidad propia mediante el reconocimiento internacional a autores como los premios Nobel Derek Walcott (Santa Lucía) y V. S. Naipaul (Trinidad y Tobago), entre otros. El perfil de la producción cinematográfica de la región, sin embargo, es más modesto, aunque el cine ha sido un eje fundamental de la cultura del Caribe, donde el papel de Hollywood como “fábrica de sueños” ha dejado una huella indeleble en las formas expresivas de varias generaciones. El cine hace aparición en la literatura de la región con extraordinaria frecuencia; a su vez, el cine autóctono se sirve tanto del otro cine, el hollywoodense, como de la propia literatura de la región mediante adaptaciones. En este ensayo exploramos la influencia mutua entre cine y literatura y su relevancia para el desarrollo identitario del Caribe angloparlante.

OBJECTIVE: The purpose of this study was to find loci for major depression via linkage analysis of a large sibling pair sample. METHOD: The authors conducted a genome-wide linkage analysis of 839 families consisting of 971 affected sibling pairs with severe recurrent major depression, comprising waves I and II of the Depression Network Study cohort. In addition to examining affected status, linkage analyses in the full data set were performed using diagnoses restricted by impairment severity, and association mapping of hits in a large case-control data set was attempted. RESULTS: The authors identified genome-wide significant linkage to chromosome 3p25-26 when the diagnoses were restricted by severity, which was a maximum LOD score of 4.0 centered at the linkage marker D3S1515. The linkage signal identified was genome-wide significant after correction for the multiple phenotypes tested, although subsequent association mapping of the region in a genome-wide association study of a U.K. depression sample did not provide significant results. CONCLUSIONS: The authors report a genome-wide significant locus for depression that implicates genes that are highly plausible for involvement in the etiology of recurrent depression. Despite the fact that association mapping in the region was negative, the linkage finding was replicated by another group who found genome-wide-significant linkage for depression in the same region. This suggests that 3p25-26 is a new locus for severe recurrent depression. This represents the first report of a genome-wide significant locus for depression that also has an independent genome-wide significant replication.

Bipolar disorder (BD) is a complex genetic disease for which the underlying pathophysiology has yet to be fully explained. 5,10-Methylenetetrahydrofolate reductase (MTHFR) is a crucial enzyme in folate-mediated one-carbon metabolism and folate deficiency can be associated with psychiatric symptoms. A single base variant in MTHFR gene (C677T) results in the production of a mildly dysfunctional thermolabile enzyme and has recently been implicated in BD. We conducted an association study of this polymorphism in 897 patients with bipolar I or bipolar II disorder, and 1,687 healthy control subjects. We found no evidence for genotypic or allelic association in this sample. We also performed a meta-analysis of our own, and all published data, and report no evidence for association. Our findings suggest that the MTHFR C677T polymorphism is not involved in the genetic etiology of clinically significant BD.

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It has been suggested that alteration in the muscarinic-cholinergic system is involved in modulation of mood. Three studies have reported linkage on chromosome 7 with major depressive disorder (MDD) in or close to a region containing the muscarinic receptor CHRM2 gene. A haplotype of SNPs located in CHRM2 (rs1824024-rs2061174-rs324650) has been significantly associated with MDD in a previous study. We report the first study investigating this gene in a large, adequately powered, clinical depression case-control sample (n = 1420 cases, 1624 controls). Our data fail to support association with the CHRM2 polymorphisms previously implicated in the genetic aetiology of depression. It is possible our failure to replicate may be a consequence of differences in definition of the MDD phenotype and/or ethnic differences.

The objective of the Genome-based Therapeutic Drugs for Depression study is to investigate the function of variations in genes encoding key proteins in serotonin, norepinephrine, neurotrophic and glucocorticoid signaling in determining the response to serotonin-reuptake-inhibiting and norepinephrine-reuptake-inhibiting antidepressants. A total of 116 single nucleotide polymorphisms in 10 candidate genes were genotyped in 760 adult patients with moderate-to-severe depression, treated with escitalopram (a serotonin reuptake inhibitor) or nortriptyline (a norepinephrine reuptake inhibitor) for 12 weeks in an open-label part-randomized multicenter study. The effect of genetic variants on change in depressive symptoms was evaluated using mixed linear models. Several variants in a serotonin receptor gene (HTR2A) predicted response to escitalopram with one marker (rs9316233) explaining 1.1% of variance (P = 0.0016). Variants in the norepinephrine transporter gene (SLC6A2) predicted response to nortriptyline, and variants in the glucocorticoid receptor gene (NR3C1) predicted response to both antidepressants. Two HTR2A markers remained significant after hypothesis-wide correction for multiple testing. A false discovery rate of 0.106 for the three strongest associations indicated that the multiple findings are unlikely to be false positives. The pattern of associations indicated a degree of specificity with variants in genes encoding proteins in serotonin signaling influencing response to the serotonin-reuptake-inhibiting escitalopram, genes encoding proteins in norepinephrine signaling influencing response to the norepinephrine-reuptake-inhibiting nortriptyline and a common pathway gene influencing response to both antidepressants. The single marker associations explained only a small proportion of variance in response to antidepressants, indicating a need for a multivariate approach to prediction., SCOPUS: ar.j, info:eu-repo/semantics/published

The aircraft is an Aerocommander 690A twin fitted with TPE331 Garrett 700 horse power turbine engines. It is owned by the South African Weather Service (SAWS) and operated by Orsmond Aviation Ltd South Africa. The cruise speed of the aircraft is approximately 150 knots and the aircraft is well suited to weather research applications. The aircraft was built in the mid 1970s and has been operated for meteorological research purposes by staff the South African Weather Service (SAWS) and the University of Witswatersrand for approximately twenty years. Scientific instrumentation described in this manual are the instruments which have been mounted aboard the SAWS Aerocommander 690A. The aircraft has a registration ZS-JRA and whilst in operation during the Queensland Government Cloud Seeding Research Project (QCSRP) has a designated call sign “SEEDA1”.

With increasing environmental concern and focus on irrigation water use efficiency, there is now considerable pressure on us all to optimise, as far as possible, the use of our most precious resource: water. The rate of evaporation is in excess of 2 m per year over most of Australia’s landmass and mean rainfall in Australia is less than 500 mm per year and falling. It has been estimated that up to 95 per cent of the rain which falls in Australia evaporates and does not contribute to runoff. When harvested, water is commonly stored in small storages and dams, but it is estimated that up to half of this may be lost to evaporation. This represents a huge waste of our resource. The price and value of water are increasing dramatically and the scarcity of water is the main limiting factor working against agricultural production in Australia. Australia has approximately 500 large dams with a combined capacity of 80 000 GL, roughly equivalent to four times the annual amount of surface water diverted (NLWRA 2001a). Australia has several million farm dams which account for an estimated 9 per cent of the total water stored, or approximately 7000 GL (Environment Australia 2000). Assuming that these small dams on average contain water only 50 per cent of the time, and assuming that 40 per cent of this is lost to evaporation, it can therefore be roughly argued that the total agricultural water lost to evaporation is probably around 1400 GL. There is great uncertainty in this figure however, as the last two quantities are largely unknown. A scoping style research study is urgently required to obtain more accurate and quantitative data in this area. The amount of water lost to evaporation from storages depends on many factors including atmospheric evaporative demand, the size of the water storage and storage method. There have been many attempts to reduce evaporation losses by altering how the water is stored. Water loss from storage dams can firstly be managed by increasing their