Integrating personality research and animal contest theory: aggressiveness in the green swordtail <i>Xiphophorus helleri</i>

&lt;p&gt;Aggression occurs when individuals compete over limiting resources. While theoretical studies have long placed a strong emphasis on context-specificity of aggression, there is increasing recognition that consistent behavioural differences exist among individuals, and that aggressiveness may be an important component of individual personality. Though empirical studies tend to focus on one aspect or the other, we suggest there is merit in modelling both within-and among-individual variation in agonistic behaviour simultaneously. Here, we demonstrate how this can be achieved using multivariate linear mixed effect models. Using data from repeated mirror trials and dyadic interactions of male green swordtails, &lt;i&gt;Xiphophorus helleri&lt;/i&gt;, we show repeatable components of (co)variation in a suite of agonistic behaviour that is broadly consistent with a major axis of variation in aggressiveness. We also show that observed focal behaviour is dependent on opponent effects, which can themselves be repeatable but were more generally found to be context specific. In particular, our models show that within-individual variation in agonistic behaviour is explained, at least in part, by the relative size of a live opponent as predicted by contest theory. Finally, we suggest several additional applications of the multivariate models demonstrated here. These include testing the recently queried functional equivalence of alternative experimental approaches, (e. g., mirror trials, dyadic interaction tests) for assaying individual aggressiveness.&lt;/p&gt

Discovering joint associations between disease and gene pairs with a novel similarity test

Genes in a functional pathway can have complex interactions. A gene might activate or suppress another gene, so it is of interest to test joint associations of gene pairs. To simultaneously detect the joint association between disease and two genes (or two chromosomal regions), we propose a new test with the use of genomic similarities. Our test is designed to detect epistasis in the absence of main effects, main effects in the absence of epistasis, or the presence of both main effects and epistasis. Results: The simulation results show that our similarity test with the matching measure is more powerful than the Pearson's chi(2) test when the disease mutants were introduced at common haplotypes, but is less powerful when the disease mutants were introduced at rare haplotypes. Our similarity tests with the counting measures are more sensitive to marker informativity and linkage disequilibrium patterns, and thus are often inferior to the similarity test with the matching measure and the Pearson 's chi(2) test. Conclusions: In detecting joint associations between disease and gene pairs, our similarity test is a complementary method to the Pearson's chi(2) test

Evaluating the effective numbers of independent tests and significant p-value thresholds in commercial genotyping arrays and public imputation reference datasets

Current genome-wide association studies (GWAS) use commercial genotyping microarrays that can assay over a million single nucleotide polymorphisms (SNPs). The number of SNPs is further boosted by advanced statistical genotype-imputation algorithms and large SNP databases for reference human populations. The testing of a huge number of SNPs needs to be taken into account in the interpretation of statistical significance in such genome-wide studies, but this is complicated by the non-independence of SNPs because of linkage disequilibrium (LD). Several previous groups have proposed the use of the effective number of independent markers (Me) for the adjustment of multiple testing, but current methods of calculation for Me are limited in accuracy or computational speed. Here, we report a more robust and fast method to calculate Me. Applying this efficient method [implemented in a free software tool named Genetic type 1 error calculator (GEC)], we systematically examined the Me, and the corresponding p-value thresholds required to control the genome-wide type 1 error rate at 0.05, for 13 Illumina or Affymetrix genotyping arrays, as well as for HapMap Project and 1000 Genomes Project datasets which are widely used in genotype imputation as reference panels. Our results suggested the use of a p-value threshold of ~10−7 as the criterion for genome-wide significance for early commercial genotyping arrays, but slightly more stringent p-value thresholds ~5 × 10−8 for current or merged commercial genotyping arrays, ~10−8 for all common SNPs in the 1000 Genomes Project dataset and ~5 × 10−8 for the common SNPs only within genes

Gene-Based Tests of Association

Genome-wide association studies (GWAS) are now used routinely to identify SNPs associated with complex human phenotypes. In several cases, multiple variants within a gene contribute independently to disease risk. Here we introduce a novel Gene-Wide Significance (GWiS) test that uses greedy Bayesian model selection to identify the independent effects within a gene, which are combined to generate a stronger statistical signal. Permutation tests provide p-values that correct for the number of independent tests genome-wide and within each genetic locus. When applied to a dataset comprising 2.5 million SNPs in up to 8,000 individuals measured for various electrocardiography (ECG) parameters, this method identifies more validated associations than conventional GWAS approaches. The method also provides, for the first time, systematic assessments of the number of independent effects within a gene and the fraction of disease-associated genes housing multiple independent effects, observed at 35%–50% of loci in our study. This method can be generalized to other study designs, retains power for low-frequency alleles, and provides gene-based p-values that are directly compatible for pathway-based meta-analysis

Understanding Variation in Sets of N-of-1 Trials.

A recent paper in this journal by Chen and Chen has used computer simulations to examine a number of approaches to analysing sets of n-of-1 trials. We have examined such designs using a more theoretical approach based on considering the purpose of analysis and the structure as regards randomisation that the design uses. We show that different purposes require different analyses and that these in turn may produce quite different results. Our approach to incorporating the randomisation employed when the purpose is to test a null hypothesis of strict equality of the treatment makes use of Nelder's theory of general balance. However, where the purpose is to make inferences about the effects for individual patients, we show that a mixed model is needed. There are strong parallels to the difference between fixed and random effects meta-analyses and these are discussed

Genetic Determinants of Cardiovascular Events among Women with Migraine: A Genome-Wide Association Study

Migraine is associated with an increased risk for cardiovascular disease (CVD). Both migraine and CVD are highly heritable. However, the genetic liability for CVD among migraineurs is unclear.We performed a genome-wide association study for incident CVD events during 12 years of follow-up among 5,122 migraineurs participating in the population-based Women's Genome Health Study. Migraine was self-reported and CVD events were confirmed after medical records review. We calculated odds ratios (OR) and 95% confidence intervals (CI) and considered a genome-wide p-value <5×10(-8) as significant.Among the 5,122 women with migraine 164 incident CVD events occurred during follow-up. No SNP was associated with major CVD, ischemic stroke, myocardial infarction, or CVD death at the genome-wide level; however, five SNPs showed association with p<5×10(-6). Among migraineurs with aura rs7698623 in MEPE (OR = 6.37; 95% CI 3.15-12.90; p = 2.7×10(-7)) and rs4975709 in IRX4 (OR = 5.06; 95% CI 2.66-9.62; p = 7.7×10(-7)) appeared to be associated with ischemic stroke, rs2143678 located close to MDF1 with major CVD (OR = 3.05; 95% CI 1.98-4.69; p = 4.3×10(-7)), and the intergenic rs1406961 with CVD death (OR = 12.33; 95% CI 4.62-32.87; p = 5.2×10(-7)). Further, rs1047964 in BACE1 appeared to be associated with CVD death among women with any migraine (OR = 4.67; 95% CI 2.53-8.62; p = 8.0×10(-7)).Our results provide some suggestion for an association of five SNPs with CVD events among women with migraine; none of the results was genome-wide significant. Four associations appeared among migraineurs with aura, two of those with ischemic stroke. Although our population is among the largest with migraine and incident CVD information, these results must be treated with caution, given the limited number of CVD events among women with migraine and the low minor allele frequencies for three of the SNPs. Our results await independent replication and should be considered hypothesis generating for future research

Juvenile Greylag Geese (Anser anser) Discriminate between Individual Siblings

Social species that maintain individualised relationships with certain others despite continuous changes in age, reproductive status and dominance rank between group members ought to be capable of individual recognition. Tests of “true” individual recognition, where an individual recognises unique features of another, are rare, however. Often kinship and/or familiarity suffice to explain dyadic interactions. The complex relationships within a greylag goose flock suggest that they should be able to recognise individuals irrespective of familiarity or kinship. We tested whether six-week-old hand-raised greylags can discriminate between two of their siblings. We developed a new experimental protocol, in which geese were trained to associate social siblings with geometrical symbols. Subsequently, focals were presented with two geometrical symbols in the presence of a sibling associated with one of the symbols. Significant choice of the geometrical symbol associated with the target present indicated that focals were able to distinguish between individual targets. Greylag goslings successfully learned this association-discrimination task, regardless of genetic relatedness or sex of the sibling targets. Social relationships within a goose flock thus may indeed be based on recognition of unique features of individual conspecifics

A randomised controlled trial of the Neuro Emotional Technique (NET) for childhood Attention Deficit Hyperactivity Disorder (ADHD): a protocol

<p>Abstract</p> <p>Background</p> <p>An abundance of literature is dedicated to research for the treatment of Attention Deficit Hyperactivity Disorder (ADHD). Most, is in the area of pharmacological therapies with less emphasis in psychotherapy and psychosocial interventions and even less in the area of complementary and alternative medicine (CAM).</p> <p>The use of CAM has increased over the years, especially for developmental and behavioral disorders, such as ADHD. 60–65% of parents with children with ADHD have used CAM. Medical evidence supports a multidisciplinary approach (i.e. pharmacological and psychosocial) for the best clinical outcomes. The Neuro Emotional Technique (NET), a branch of Chiropractic, was designed to address the biopsychosocial aspects of acute and chronic conditions including non-musculoskeletal conditions. Anecdotally, it has been suggested that ADHD may be managed effectively by NET.</p> <p>Design/methods</p> <p>A placebo controlled, double blind randomised clinical trial was designed to assess the effectiveness of NET on a cohort of children with medically diagnosed ADHD.</p> <p>Children aged 5–12 years who met the inclusion criteria were randomised to one of three groups. The control group continued on their existing medical regimen and the intervention and placebo groups had the addition of the NET and sham NET protocols added to their regimen respectively. These two groups attended a clinical facility twice a week for the first month and then once a month for six months.</p> <p>The Conners' Parent and Teacher Rating Scales (CRS) were used at the start of the study to establish baseline data and then in one month and in seven months time, at the conclusion of the study. The primary outcome measures chosen were the Conners' ADHD Index and Conners' Global Index. The secondary outcome measures chosen were the DSM-IV: Inattentive, the DSM-IV:Hyperactive-Impulsive, and the DSM-IV:Total subscales from the Conners' Rating Scales, monitoring changes in inattention, hyperactivity and impulsivity.</p> <p>Calculations for the sample size were set with a significance level of 0.05 and the power of 80%, yielding a sample size of 93.</p> <p>Discussion</p> <p>The present study should provide information as to whether the addition of NET to an existing medical regimen can improve outcomes for children with ADHD.</p> <p>Trial registration</p> <p>Australian New Zealand Clinical Trial Registration Number: ANZCTRN 012606000332527</p