Consistently replicating locus linked to migraine on 10q22-q23

Here, we present the results of two genome-wide scans in two diverse populations in which a consistent use of recently introduced migraine-phenotyping methods detects and replicates a locus on 10q22-q23, with an additional independent replication. No genetic variants have been convincingly established in migraine, and although several loci have been reported, none of them has been consistently replicated. We employed the three known migraine-phenotyping methods (clinical end diagnosis, latent-class analysis, and trait-component analysis) with robust multiple testing correction in a large sample set of 1675 individuals from 210 migraine families from Finland and Australia. Genome-wide multipoint linkage analysis that used the Kong and Cox exponential model in Finns detected a locus on 10q22-q23 with highly significant evidence of linkage (LOD 7.68 at 103 cM in female-specific analysis). The Australian sample showed a LOD score of 3.50 at the same locus (100 cM), as did the independent Finnish replication study (LOD score 2.41, at 102 cM). In addition, four previously reported loci on 8q21, 14q21, 18q12, and Xp21 were also replicated. A shared-segment analysis of 10q22-q23 linked Finnish families identified a 1.6-9.5 cM segment, centered on 101 cM, which shows in-family homology in 95% of affected Finns. This region was further studied with 1323 SNPs. Although no significant association was observed, four regions warranting follow-up studies were identified. These results support the use of symptomology-based phenotyping in migraine and suggest that the 10q22-q23 locus probably contains one or more migraine susceptibility variants.

Migraine with aura and migraine without aura are not distinct entities: further evidence from a large Dutch population study

It is often debated whether migraine with aura (MA) and migraine without aura (MO) are etiologically distinct disorders. A previous study using latent class analysis (LCA) in Australian twins showed no evidence for separate subtypes of MO and MA. The aim of the present study was to replicate these results in a population of Dutch twins and their parents, siblings and partners (N = 10,144). Latent class analysis of International Headache Society (IHS)-based migraine symptoms resulted in the identification of 4 classes: a class of unaffected subjects (class 0), a mild form of nonmigrainous headache (class 1), a moderately severe type of migraine (class 2), typically without neurological symptoms or aura (8% reporting aura symptoms), and a severe type of migraine (class 3), typically with neurological symptoms, and aura symptoms in approximately half of the cases. Given the overlap of neurological symptoms and nonmutual exclusivity of aura symptoms, these results do not support the MO and MA subtypes as being etiologically distinct. The heritability in female twins of migraine based on LCA classification was estimated at .50 (95% confidence intervals [CI] .27 - .59), similar to IHS-based migraine diagnosis (h2 = .49, 95% CI .19-.57). However, using a dichotomous classification (affected-unaffected) decreased heritability for the IHS-based classification (h2 = .33, 95% CI .00-.60), but not the LCA-based classification (h2 = .51, 95% CI .23-.61). Importantly, use of the LCA-based classification increased the number of subjects classified as affected. The heritability of the screening question was similar to more detailed LCA and IHS classifications, suggesting that the screening procedure is an important determining factor in genetic studies of migraine.

Genomewide significant linkage to migrainous headache on chromosome 5q21

Familial typical migraine is a common, complex disorder that shows strong familial aggregation. Using latent-class analysis (LCA), we identified subgroups of people with migraine/severe headache in a community sample of 12,245 Australian twins (60% female), drawn from two cohorts of individuals aged 23-90 years who completed an interview based on International Headache Society criteria. We report results from genomewide linkage analyses involving 756 twin families containing a total of 790 independent sib pairs (130 affected concordant, 324 discordant, and 336 unaffected concordant for LCA-derived migraine). Quantitative-trait linkage analysis produced evidence of significant linkage on chromosome 5q21 and suggestive linkage on chromosomes 8, 10, and 13. In addition, we replicated previously reported typical-migraine susceptibility loci on chromosomes 6p12.2-p21.1 and 1q21-q23, the latter being within 3 cM of the rare autosomal dominant familial hemiplegic migraine gene (ATP1A2), a finding which potentially implicates ATP1A2 in familial typical migraine for the first time. Linkage analyses of individual migraine symptoms for our six most interesting chromosomes provide tantalizing hints of the phenotypic and genetic complexity of migraine. Specifically, the chromosome 1 locus is most associated with phonophobia; the chromosome 5 peak is predominantly associated with pulsating headache; the chromosome 6 locus is associated with activity-prohibiting headache and photophobia; the chromosome 8 locus is associated with nausea/vomiting and moderate/severe headache; the chromosome 10 peak is most associated with phonophobia and photophobia; and the chromosome 13 peak is completely due to association with photophobia. These results will prove to be invaluable in the design and analysis of future linkage and linkage disequilibrium studies of migraine.

Early childhood profiles of sleep problems and self-regulation predict later school adjustment

Background Children’s sleep problems and self-regulation problems have been independently associated with poorer adjustment to school, but there has been limited exploration of longitudinal early childhood profiles that include both indicators. Aims This study explores the normative developmental pathway for sleep problems and self-regulation across early childhood, and investigates whether departure from the normative pathway is associated with later social-emotional adjustment to school. Sample This study involved 2880 children participating in the Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) – Infant Cohort from Wave 1 (0-1 years) to Wave 4 (6-7 years). Method Mothers reported on children’s sleep problems, emotional, and attentional self-regulation at three time points from birth to 5 years. Teachers reported on children’s social-emotional adjustment to school at 6-7 years. Latent profile analysis was used to establish person-centred longitudinal profiles. Results Three profiles were found. The normative profile (69%) had consistently average or higher emotional and attentional regulation scores and sleep problems that steadily reduced from birth to 5. The remaining 31% of children were members of two non-normative self-regulation profiles, both characterised by escalating sleep problems across early childhood and below mean self-regulation. Non-normative group membership was associated with higher teacher-reported hyperactivity and emotional problems, and poorer classroom self-regulation and prosocial skills. Conclusion Early childhood profiles of self-regulation that include sleep problems offer a way to identify children at risk of poor school adjustment. Children with escalating early childhood sleep problems should be considered an important target group for school transition interventions.

Human action recognition from video sequences

This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.

The nexus between poverty and deprivation in Vietnam

Unlike previous studies’ finding on western and developed economies, income is a significant determinant of multidimensional deprivation in Vietnam. This first study on a developing country also incorporates food security in a latent class framework to compute a new multidimensional deprivation index. It was found that chronic poverty and not transient poverty has a detrimental effect on multidimensional deprivation and thus current poverty alleviation programs should potentially be tailored according to these poverty types to effectively combat multidimensional deprivation. The finding that 20% of non-poor are most deprived with85% of this group living in urban Vietnam also points to the need for a new form of targeted policy.

Complexity of collaborative work in residential aged care facilities: An analysis of information exchange for medication management

Information exchange (IE) is a critical component of the complex collaborative medication process in residential aged care facilities (RACFs). Designing information and communication technology (ICT) to support complex processes requires a profound understanding of the IE that underpins their execution. There is little existing research that investigates the complexity of IE in RACFs and its impact on ICT design. The aim of this study was thus to undertake an in-depth exploration of the IE process involved in medication management to identify its implications for the design of ICT. The study was undertaken at a large metropolitan facility in NSW, Australia. A total of three focus groups, eleven interviews and two observation sessions were conducted between July to August 2010. Process modelling was undertaken by translating the qualitative data via in-depth iterative inductive analysis. The findings highlight the complexity and collaborative nature of IE in RACF medication management. These models emphasize the need to: a) deal with temporal complexity; b) rely on an interdependent set of coordinative artefacts; and c) use synchronous communication channels for coordination. Taken together these are crucial aspects of the IE process in RACF medication management that need to be catered for when designing ICT in this critical area. This study provides important new evidence of the advantages of viewing process as a part of a system rather than as segregated tasks as a means of identifying the latent requirements for ICT design and that is able to support complex collaborative processes like medication management in RACFs. © 2012 IEEE.

Beyond Gauss: Image-set matching on the Riemannian manifold of PDFs

State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution functions (PDFs) using kernel density estimators. To compare and match image-sets, we exploit Csiszar´ f-divergences, which bear strong connections to the geodesic distance defined on the space of PDFs, i.e., the statistical manifold. Furthermore, we introduce valid positive definite kernels on the statistical manifold, which let us make use of more powerful classification schemes to match image-sets. Finally, we introduce a supervised dimensionality reduction technique that learns a latent space where f-divergences reflect the class labels of the data. Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.

Elliptical summary randomisation for sensor-based human activity recognition

Many conventional statistical machine learning al- gorithms generalise poorly if distribution bias ex- ists in the datasets. For example, distribution bias arises in the context of domain generalisation, where knowledge acquired from multiple source domains need to be used in a previously unseen target domains. We propose Elliptical Summary Randomisation (ESRand), an efficient domain generalisation approach that comprises of a randomised kernel and elliptical data summarisation. ESRand learns a domain interdependent projection to a la- tent subspace that minimises the existing biases to the data while maintaining the functional relationship between domains. In the latent subspace, ellipsoidal summaries replace the samples to enhance the generalisation by further removing bias and noise in the data. Moreover, the summarisation enables large-scale data processing by significantly reducing the size of the data. Through comprehensive analysis, we show that our subspace-based approach outperforms state-of-the-art results on several activity recognition benchmark datasets, while keeping the computational complexity significantly low.

Translating emotional insights into digital channel designs: Opportunities to enhance the airport experience

Purpose The purpose of this study is to identify and understand the emotions behind a passenger’s airport experience and how this can inform digital channel engagements. Design/methodology/approach This study investigates the emotional experience of two hundred (200) passengers’ journeys at an Australian domestic airport. A survey was conducted which implemented the use of Emocards and an interview approach of laddering. The responses were then analysed into attributes, consequences and values. Findings The results indicate that across key stages of the airport (parking, retail, gates and arrivals) passengers had different emotional experiences (positive, negative and neutral). The attributes, consequences and values behind these emotions were then used to propose digital channel content and purpose of various future digital channel engagements. Research limitations/implications By gaining emotional insights airports are able to generate digital channel engagements, which align with passengers’ needs and values rather than internal operational motivations. Theoretical contributions include the development of the Technology Acceptance Model to include emotional drivers as influences in the use of digital channels. Originality/value This research provides a unique method to understand the passengers’ emotional journey across the airport infrastructure and suggest how to better design digital channel engagements to address passenger latent needs.

The profile of psychiatric symptoms exacerbated by methamphetamine use

Background Methamphetamine use can produce symptoms almost indistinguishable from schizophrenia. Distinguishing between the two conditions has been hampered by the lack of a validated symptom profile for methamphetamine-induced psychiatric symptoms. We use data from a longitudinal cohort study to examine the profile of psychiatric symptoms that are acutely exacerbated by methamphetamine use. Methods 164 methamphetamine users, who did not meet DSM-IV criteria for a lifetime primary psychotic disorder, were followed monthly for one year to assess the relationship between days of methamphetamine use and symptom severity on the 24-item Brief Psychiatric Rating Scale. Exacerbation of psychiatric symptoms with methamphetamine use was quantified using random coefficient models. The dimensions of symptom exacerbation were examined using principal axis factoring and a latent profile analysis. Results Symptoms exacerbated by methamphetamine loaded on three factors: positive psychotic symptoms (suspiciousness, unusual thought content, hallucinations, bizarre behavior); affective symptoms (depression, suicidality, guilt, hostility, somatic concern, self-neglect); and psychomotor symptoms (tension, excitement, distractibility, motor hyperactivity). Methamphetamine use did not significantly increase negative symptoms. Vulnerability to positive psychotic and affective symptom exacerbation was shared by 28% of participants, and this vulnerability aligned with a past year DSM-IV diagnosis of substance-induced psychosis (38% vs. 22%, _2 (df1) = 3.66, p = 0.056). Conclusion Methamphetamine use produced a symptom profile comprised of positive psychotic and affective symptoms, which aligned with a diagnosis of substance-induced psychosis, with no evidence of a negative syndrome.

Is the mental wellbeing of young Australians best represented by a single, multidimensional or bifactor model?

Internationally there is a growing interest in the mental wellbeing of young people. However, it is unclear whether mental wellbeing is best conceptualized as a general wellbeing factor or a multidimensional construct. This paper investigated whether mental wellbeing, measured by the Mental Health Continuum-Short Form (MHC-SF), is best represented by: (1) a single-factor general model; (2) a three-factor multidimensional model or (3) a combination of both (bifactor model). 2,220 young Australians aged between 16 and 25 years completed an online survey including the MHC-SF and a range of other wellbeing and mental ill-health measures. Exploratory factor analysis supported a bifactor solution, comprised of a general wellbeing factor, and specific group factors of psychological, social and emotional wellbeing. Confirmatory factor analysis indicated that the bifactor model had a better fit than competing single and three-factor models. The MHC-SF total score was more strongly associated with other wellbeing and mental ill-health measures than the social, emotional or psychological subscale scores. Findings indicate that the mental wellbeing of young people is best conceptualized as an overarching latent construct (general wellbeing) to which emotional, social and psychological domains contribute. The MHC-SF total score is a valid and reliable measure of this general wellbeing factor.

Does gender moderate the relationship between polydrug use and sexual risk-taking among Australian secondary school students under 16 years of age?

Introduction and Aims This study examines the association of alcohol and polydrug use with risky sexual behaviour in adolescents under 16 years of age and if this association differs by gender. Design and Methods The sample consisted of 5412 secondary school students under 16 years of age from Victoria, Australia. Participants completed an anonymous and confidential survey during class time. The key measures were having had sex before legal age of consent (16 years), unprotected sex before 16 (no condom) and latent-class derived alcohol and polydrug use variables based on alcohol, tobacco, cannabis, inhalants and other illegal drug use in the past month. Results There were 7.52% and 2.55% of adolescents who reported having sex and having unprotected sex before 16 years of age, respectively. After adjusting for antisocial behaviours, peers' drug use and family and school risk factors, girls were less likely to have unprotected sex (odds ratio = 0.31, P = 0.003). However, the interaction of being female and polydrug use (odds ratio = 4.52, P = 0.004) was significant, indicating that girls who engaged in polydrug use were at higher risk of having unprotected sex. For boys, the effect of polydrug use was non-significant (odds ratio = 1.44, P = 0.310). Discussion and Conclusions For girls, polydrug use was significantly associated with unprotected sex after adjusting for a range of risk factors, and this relationship was non-significant for boys. Future prevention programs for adolescent risky sexual behaviour and polydrug use might benefit from a tailored approach to gender differences.