Service user satisfaction with care in a specialist service for young people with attention deficit hyperactivity disorder

OBJECTIVES

Consumer satisfaction is considered one of the most important measures of service quality in child mental health; however, there is limited understanding of factors that influence satisfaction. The objective of this study was to investigate key factors influencing satisfaction with care (SWC) in ADMiRE, a specialist service for young people (YP) with attention deficit hyperactivity disorder (ADHD).

METHODS

Parents/carers (n = 67) and YP > 9 years (n = 44) attending ADMiRE completed an anonymous Experience of Service Questionnaire (ESQ), a quantitative/qualitative measure of service user satisfaction. Parents/carers also completed symptom severity rating scales. Data were analysed to determine (i) overall SWC, (ii) the relationship between parent- and youth-reported SWC and (iii) the impact of symptom severity on SWC. Thematic analysis of qualitative ESQ data was completed.

RESULTS

Parents/carers were significantly more satisfied than YP (p = 0.028). Symptom severity did not impact significantly on parent/carer satisfaction. YP with severe hyperactive/impulsive and inattentive ADHD symptoms were significantly less satisfied with care than those with less severe ADHD symptoms (p = 0.022 and p = 0.017 respectively). Factors related to the therapeutic alliance were identified as being particularly important to both parents/carers and YP.

CONCLUSIONS

This is the first Irish study that has investigated the impact of symptom severity on service user satisfaction in a child mental health service. The results highlight the different perspectives of YP and parents and provide novel insights into the impact of symptom severity on service user satisfaction. The importance of the therapeutic alliance should not be underestimated in future development of services.

P53 and TLR4 expression are prognostic markers informing progression free survival of advanced stage high grade serous ovarian cancer

OBJECTIVE

New prognostic biomarkers, and bio-signatures, are urgently needed to facilitate a precision medicine-based approach to more effectively treat patients with high-grade serous ovarian cancer (HGSC). In this study, we analysed the expression patterns of a series of candidate protein biomarkers.

METHODS

The panel of markers which included MyD88, TLR4, MAD2, PR, OR, WT1, p53, p16, CD10 and Ki67 was assessed using immunohistochemistry in a tissue microarray (TMA) cohort of n = 80 patients, composed of stage 3-4 HGSCs. Each marker was analysed for their potential to predict both overall survival (OS) and progression-free survival (PFS).

RESULTS

TLR4 and p53 were found to be individually predictive of poorer PFS (Log Rank, p = 0.017, p = 0.030 respectively). Cox regression analysis also identified high p53 and TLR4 expression as prognostic factors for reduced PFS (p53; HR=1.785, CI=1.036-3.074, p = 0.037 and TLR4; HR=2.175, CI=1.112-4.253, p = 0.023). Multivariate forward conditional Cox regression analysis, examining all markers, identified a combined signature composed of p53 and TLR4 as prognostic for reduced PFS (p = 0.023).

CONCLUSION

Combined p53 and TLR4 marker assessment may help to aid treatment stratification for patients diagnosed with advanced-stage HGSC.

Ultrarare Missense Variants Implicated in Utah Pedigrees Multiply Affected With Schizophrenia

Background

Recent work from the Schizophrenia Exome Sequencing Meta-analysis (SCHEMA) consortium showed significant enrichment of ultrarare variants in schizophrenia cases. Family-based studies offer a unique opportunity to evaluate rare variants because risk in multiplex pedigrees is more likely to be influenced by the same collection of variants than an unrelated cohort.

Methods

Here, we examine whole genome sequencing data from 35 individuals across 6 pedigrees multiply affected by schizophrenia. We applied a rigorous filtering pipeline to search for classes of protein-coding variants that cosegregated with disease status, and we examined these for evidence of enrichment in the SCHEMA dataset. Additionally, we applied a family-based consensus approach to call copy number variants and screen against a list of schizophrenia-associated risk variants.

Results

We identified deleterious missense variants in 3 genes (ATP2B2, SLC25A28, and GSK3A) that cosegregated with disease in 3 of the pedigrees. In the SCHEMA, the gene ATP2B2 shows highly suggestive evidence for deleterious missense variants in schizophrenia cases (p = .000072). ATP2B2 is involved in intracellular calcium homeostasis, expressed in multiple brain tissue types, and predicted to be intolerant to loss-of-function and missense variants.

Conclusions

We have identified genes that are likely to increase schizophrenia risk in 3 of the 6 pedigrees examined, the strongest evidence being for a gene involved in calcium homeostasis. Further work is required to examine other classes of variants that may be contributing to disease burden.

Sleep problems in children and adolescents in an attention deficit hyperactivity disorder service

OBJECTIVES

Sleep problems are common amongst children and adolescents with attention deficit hyperactivity disorder (ADHD). The purpose of this study was to investigate sleep problems in children and adolescents attending a specialist ADHD service.

METHODS

This was a cross-sectional online survey combined with a retrospective chart review, conducted in the ADHD Assessment, Diagnosis, Management, initiation, Research and Education (ADMiRE) service, the first public specialist ADHD service for young people in Ireland. Participants were caregivers of children and adolescents with ADHD attending ADMiRE. Sleep was assessed using The Children's Sleep Habits Questionnaire (CSHQ) and ADHD symptoms were assessed using an abbreviated version of the Swanson, Nolan and Pelham Teacher and Parent Rating Scale (SNAP-IV). Details regarding patient demographics, co-morbidities and medication were collected from patient records.

RESULTS

Eighty-four percent of young people scored above the clinical cut-off for a sleep disorder. The most frequently reported sleep problems were related to sleep onset and sleep duration, and 64% of respondents met the criteria for two or more sleep problems. ADHD severity was associated with greater sleep problems. Co-morbid physical, neurodevelopmental, and mental health disorders as well as stimulant use were not associated with greater sleep problems.

CONCLUSION

Sleep problems are very common amongst children and adolescents with ADHD. This study has demonstrated an association between more sleep problems and ADHD severity. These findings highlight the need for both effective ADHD treatment to ensure optional sleep in young people as well as effective interventions for sleep problems to prevent worsening of ADHD symptoms.

Gender bias in academic medicine: a resumé study

BACKGROUND

Minimising the effects of unconscious bias in selection for clinical academic training is essential to ensure that allocation of training posts is based on merit. We looked at the effect of anonymising applications to a training programme for junior doctors on the scores of the applications and on gender balance; and whether female candidates were more likely to seek gender-concordant mentors.

METHODS

Applications to the training programme were reviewed and scored independently by reviewers who received either an anonymised or named copy. Scores were compared using a paired t-test, and differences in scores compared by gender. The gender of named supervisors for male and female candidates was compared.

RESULTS

Scores of 101 applications were reviewed. When their identity was known, male candidates scored 1.72% higher and female candidates scored 0.74% higher, but these findings were not statistically significant (p value = 0.279 and 0.579). Following introduction of anonymisation, the proportion of successful female candidates increased from 27 to 46%. Female candidates were more likely to name a female supervisor compared to male (41% vs. 25% of supervisors).

CONCLUSIONS

Anonymising applications did not significantly change scores, although gender balance improved. Gender-concordant mentoring initiatives should consider effects on mentors as well as mentees.

Evidence for parent-of-origin effects in autism spectrum disorder: a narrative review

Autism spectrum disorder (ASD) is a heterogeneous group of early-onset neurodevelopmental disorders known to be highly heritable with a complex genetic architecture. Abnormal brain developmental trajectories that impact synaptic functioning, excitation-inhibition balance and brain connectivity are now understood to play a central role in ASD. Ongoing efforts to identify the genetic underpinnings still prove challenging, in part due to phenotypic and genetic heterogeneity.This review focuses on parent-of-origin effects (POEs), where the phenotypic effect of an allele depends on its parental origin. POEs include genomic imprinting, transgenerational effects, mitochondrial DNA, sex chromosomes and mutational transmission bias. The motivation for investigating these mechanisms in ASD has been driven by their known impacts on early brain development and brain functioning, in particular for the most well-documented POE, genomic imprinting. Moreover, imprinting is implicated in syndromes such as Angelman and Prader-Willi, which frequently share comorbid symptoms with ASD. In addition to other regions in the genome, this comprehensive review highlights the 15q11-q13 and 7q chromosomal regions as well as the mitochondrial DNA as harbouring the majority of currently identified POEs in ASD.

Converting single nucleotide variants between genome builds: from cautionary tale to solution

Next-generation sequencing studies are dependent on a high-quality reference genome for single nucleotide variant (SNV) calling. Although the two most recent builds of the human genome are widely used, position information is typically not directly comparable between them. Re-alignment gives the most accurate position information, but this procedure is often computationally expensive, and therefore, tools such as liftOver and CrossMap are used to convert data from one build to another. However, the positions of converted SNVs do not always match SNVs derived from aligned data, and in some instances, SNVs are known to change chromosome when converted. This is a significant problem when compiling sequencing resources or comparing results across studies. Here, we describe a novel algorithm to identify positions that are unstable when converting between human genome reference builds. These positions are detected independent of the conversion tools and are determined by the chain files, which provide a mapping of contiguous positions from one build to another. We also provide the list of unstable positions for converting between the two most commonly used builds GRCh37 and GRCh38. Pre-excluding SNVs at these positions, prior to conversion, results in SNVs that are stable to conversion. This simple procedure gives the same final list of stable SNVs as applying the algorithm and subsequently removing variants at unstable positions. This work highlights the care that must be taken when converting SNVs between genome builds and provides a simple method for ensuring higher confidence converted data. Unstable positions and algorithm code, available at https://github.com/cathaloruaidh/genomeBuildConversion.

Prevalence of N-Methyl-d-Aspartate Receptor antibody (NMDAR-Ab) encephalitis in patients with first episode psychosis and treatment resistant schizophrenia on clozapine, a population based study

INTRODUCTION

N-methyl-d-aspartate receptor antibody (NMDAR-Ab) encephalitis consensus criteria has recently been defined. We aimed to examine the prevalence of NMDAR-Ab encephalitis in patients with first episode psychosis (FEP) and treatment resistant schizophrenia (TRS) on clozapine, using clinical investigations, antibody testing and to retrospectively apply diagnostic consensus criteria.

METHODS

Adult (18-65 years old) cases of FEP meeting inclusion criteria were recruited over three years and assessed using the Structured Clinical Interview for DSM-IV disorders (SCID). NMDAR-Ab was identified using a live cell-based assay (L-CBA). Seropositive cases were clinically investigated for features of encephalitis including neuro-imaging, EEG and CSF where possible. Serum was retested using immunohistochemistry (IHC) as part of diagnostic criteria guidelines. A cohort of patients with TRS was also recruited.

RESULTS

112 FEP patients were recruited over 3 years. NMDAR-Ab seroprevalence was 4/112 (3.5%) cases. One case (<1%) was diagnosed with definite NMDAR-Ab encephalitis and treated with immunotherapy. One of the three other seropositive cases met criteria for probable encephalitis. However all three were ultimately diagnosed with mood disorders with psychotic features. None have developed neurological features at three year follow up. 1/100 (1%) of patients with TRS was 100 patients with TRS were recruited. One case (1%) seropositive for NMDAR-Ab but did not meet criteria for encephalitis.

CONCLUSIONS

NMDAR-Ab encephalitis as defined by consensus guidelines occured rarely in psychiatric services in this study. Further studies are needed to establish pathogenicity of serum NMDAR-Ab antibodies. Psychiatric services should be aware of the clinical features of encephalitis.

Identifying schizophrenia patients who carry pathogenic genetic copy number variants using standard clinical assessment: retrospective cohort study

BACKGROUND

Copy number variants (CNVs) play a significant role in disease pathogenesis in a small subset of individuals with schizophrenia (~2.5%). Chromosomal microarray testing is a first-tier genetic test for many neurodevelopmental disorders. Similar testing could be useful in schizophrenia.

AIMS

To determine whether clinically identifiable phenotypic features could be used to successfully model schizophrenia-associated (SCZ-associated) CNV carrier status in a large schizophrenia cohort.

METHOD

Logistic regression and receiver operating characteristic (ROC) curves tested the accuracy of readily identifiable phenotypic features in modelling SCZ-associated CNV status in a discovery data-set of 1215 individuals with psychosis. A replication analysis was undertaken in a second psychosis data-set (n = 479).

RESULTS

In the discovery cohort, specific learning disorder (OR = 8.12; 95% CI 1.16-34.88, P = 0.012), developmental delay (OR = 5.19; 95% CI 1.58-14.76, P = 0.003) and comorbid neurodevelopmental disorder (OR = 5.87; 95% CI 1.28-19.69, P = 0.009) were significant independent variables in modelling positive carrier status for a SCZ-associated CNV, with an area under the ROC (AUROC) of 74.2% (95% CI 61.9-86.4%). A model constructed from the discovery cohort including developmental delay and comorbid neurodevelopmental disorder variables resulted in an AUROC of 83% (95% CI 52.0-100.0%) for the replication cohort.

CONCLUSIONS

These findings suggest that careful clinical history taking to document specific neurodevelopmental features may be informative in screening for individuals with schizophrenia who are at higher risk of carrying known SCZ-associated CNVs. Identification of genomic disorders in these individuals is likely to have clinical benefits similar to those demonstrated for other neurodevelopmental disorders.

Evidence of Assortative Mating in Autism Spectrum Disorder

BACKGROUND

Assortative mating is a nonrandom mating system in which individuals with similar genotypes and/or phenotypes mate with one another more frequently than would be expected in a random mating system. Assortative mating has been hypothesized to play a role in autism spectrum disorder (ASD) in an attempt to explain some of the increase in the prevalence of ASD that has recently been observed. ASD is considered to be a heritable neurodevelopmental disorder, but there is limited understanding of its causes. Assortative mating can be explored through both phenotypic and genotypic data, but up until now it has never been investigated through genotypic measures in ASD.

METHODS

We investigated genotypically similar mating pairs using genome-wide single nucleotide polymorphism data on trio families (Autism Genome Project data [1590 parents] and Simons Simplex Collection data [1962 parents]). To determine whether or not an excess in genetic similarity was present, we employed kinship coefficients and examined spousal correlation between the principal components in both the Autism Genome Project and Simons Simplex Collection datasets. We also examined assortative mating using phenotype data on the parents to detect any correlation between ASD traits.

RESULTS

We found significant evidence of genetic similarity between the parents of ASD offspring using both methods in the Autism Genome Project dataset. In the Simons Simplex Collection, there was also significant evidence of genetic similarity between the parents when explored through spousal correlation.

CONCLUSIONS

This study gives further support to the hypothesis that positive assortative mating plays a role in ASD.

Irish Mental Health Act 2001: impact on involuntary admissions in a community mental health service in Dublin

Aims and method

On 1 November 2006, Ireland's Mental Health Act 2001 was implemented, replacing the country's Mental Treatment Act 1945. We aimed to assess the impact of this change in legislation on the number and duration of involuntary admissions. We undertook a retrospective review of all admissions to a psychiatric admissions unit from January to October 2006 (pre-implementation) and January to October 2007 (post-implementation).

Results

There were 46 involuntary admissions in the 10-month period under study in 2006, or 33.8 per 100 000 population. There were 53 in 2007, or 39.3 per 100 000 population. This increase was not significant (z = – 0.7, P = 0.46), however involuntary admissions formed a larger proportion of all admissions under the Mental Health Act 2001 than under the Mental Treatment Act 1945 (χ2 = 4.2, P =0.04). There was no difference in the duration of involuntary admissions but under the 2001 Act, involuntary patients had longer periods of voluntary status as part of their admissions than under the 1945 Act.

Clinical implications

The introduction of more rigorous procedures for involuntary admission did not significantly change the rate or duration of involuntary admissions in our centre. The finding that involuntary admissions included longer periods of voluntary status suggests that more care is being taken to revoke involuntary admission orders under the Mental Health Act 2001 than under the Mental Treatment Act 1945.

A genome-wide investigation into parent-of-origin effects in autism spectrum disorder identifies previously associated genes including SHANK3

Autism spectrum disorder (ASD) is known to be a heritable neurodevelopmental disorder affecting more than 1% of the population but in the majority of ASD cases, the genetic cause has not been identified. Parent-of-origin effects have been highlighted as an important mechanism in the pathology of neurodevelopmental disorders such as Prader-Willi and Angelman syndrome, with individuals with these syndromes often exhibiting ASD symptoms. Consequently, systematic investigation of these effects in ASD is clearly an important line of investigation in elucidating the underlying genetic mechanisms. Using estimation of maternal, imprinting and interaction effects using multinomial modelling (EMIM), we simultaneously investigated imprinting, maternal genetic effects and associations in the Autism Genome Project and Simons Simplex Consortium genome-wide association data sets. To avoid using the overly stringent genome-wide association study significance level, we used a Bayesian threshold that takes into account the sample size, allele frequency and any available prior knowledge. Between the two data sets, we identified a total of 18 imprinting effects and 68 maternal genetic effects that met this Bayesian threshold criteria, but none met the threshold in both data sets. We identified imprinting and maternal genetic effects for regions that have previously shown evidence for parent-of-origin effects in ASD. Together with these findings, we have identified maternal genetic effects not previously identified in ASD at a locus in SHANK3 on chromosome 22 and a locus in WBSCR17 on chromosome 7 (associated with Williams syndrome). Both genes have previously been associated with ASD.

The phenotypic manifestations of rare genic CNVs in autism spectrum disorder

Significant evidence exists for the association between copy number variants (CNVs) and Autism Spectrum Disorder (ASD); however, most of this work has focused solely on the diagnosis of ASD. There is limited understanding of the impact of CNVs on the 'sub-phenotypes' of ASD. The objective of this paper is to evaluate associations between CNVs in differentially brain expressed (DBE) genes or genes previously implicated in ASD/intellectual disability (ASD/ID) and specific sub-phenotypes of ASD. The sample consisted of 1590 cases of European ancestry from the Autism Genome Project (AGP) with a diagnosis of an ASD and at least one rare CNV impacting any gene and a core set of phenotypic measures, including symptom severity, language impairments, seizures, gait disturbances, intelligence quotient (IQ) and adaptive function, as well as paternal and maternal age. Classification analyses using a non-parametric recursive partitioning method (random forests) were employed to define sets of phenotypic characteristics that best classify the CNV-defined groups. There was substantial variation in the classification accuracy of the two sets of genes. The best variables for classification were verbal IQ for the ASD/ID genes, paternal age at birth for the DBE genes and adaptive function for de novo CNVs. CNVs in the ASD/ID list were primarily associated with communication and language domains, whereas CNVs in DBE genes were related to broader manifestations of adaptive function. To our knowledge, this is the first study to examine the associations between sub-phenotypes and CNVs genome-wide in ASD. This work highlights the importance of examining the diverse sub-phenotypic manifestations of CNVs in ASD, including the specific features, comorbid conditions and clinical correlates of ASD that comprise underlying characteristics of the disorder.

DEPRESSION MEDIATES THE RELATION OF INSOMNIA SEVERITY WITH SUICIDE RISK IN THREE CLINICAL SAMPLES OF U.S. MILITARY PERSONNEL

BACKGROUND

A growing body of empirical research suggests insomnia severity is directly related to suicide ideation, attempts, and death in nonmilitary samples, even when controlling for depression and other suicide risk factors. Few studies have explored this relationship in U.S. military personnel.

METHODS

The present study entailed secondary data analyses examining the associations of insomnia severity with suicide ideation and attempts in three clinical samples: Air Force psychiatric outpatients (n = 158), recently discharged Army psychiatric inpatients (n = 168), and Army psychiatric outpatients (n = 54). Participants completed the Beck Scale for Suicide Ideation, the Beck Depression Inventory-II or Patient Health Questionnaire-9, the Insomnia Severity Index, and the Posttraumatic Stress Disorder Checklist at baseline; two samples also completed these measures during follow-up.

RESULTS

Sleep disturbance was associated with concurrent (β's > 0.21; P's < 0.059) and prospective (β's > 0.39; P's < 0.001) suicide ideation in all three samples. When adjusting for age, gender, depression, and posttraumatic stress, insomnia severity was no longer directly associated with suicide ideation either concurrently (β's < 0.19; P's > 0.200) or prospectively (β's < 0.26; P's > 0.063), but depression was (β's > 0.22; P's < 0.012). Results of a latent difference score mediation model indicated that depression mediated the relation of insomnia severity with suicide ideation.

CONCLUSIONS

Across three clinical samples of military personnel, depression explained the relationship between insomnia severity and suicide risk.

Belonging protects against postdeployment depression in military personnel

BACKGROUND

Depression among U.S. military personnel has received relatively little empirical attention compared to posttraumatic stress disorder, despite evidence that depression is associated with poor psychosocial outcomes and increased suicide risk. Even less is known about factors that protect against depression in military populations.

METHODS

A sample of 168 active duty Air Force convoy operators completed self-report measures of depression, posttraumatic stress, and sense of "belonging" before deploying to Iraq, and again at 1, 3, 6, and 12 months following their return. Linear growth modeling was used to test the associations of the variables over time.

RESULTS

Mean depression scores remained low and stable across the deployment and 12-month follow-up period. Increased depression severity was significantly associated with low belonging (P < .001) and with posttraumatic stress symptoms (P < .001) at every time point.

LIMITATIONS

Relatively small, predominantly male sample utilizing self-report methods.

CONCLUSIONS

A sense of belongingness may protect service members from depression at all stages of the deployment cycle, from predeployment preparations through deployment and postdeployment adjustment.

The phenotypic manifestations of rare CNVs in schizophrenia

There is compelling evidence for the role of copy number variants (CNVs) in schizophrenia susceptibility, and it has been estimated that up to 2-3% of schizophrenia cases may carry rare CNVs. Despite evidence that these events are associated with an increased risk across categorical neurodevelopmental disorders, there is limited understanding of the impact of CNVs on the core features of disorders like schizophrenia. Our objective was to evaluate associations between rare CNVs in differentially brain expressed (BE) genes and the core features and clinical correlates of schizophrenia. The sample included 386 cases of Irish ancestry with a diagnosis of schizophrenia, at least one rare CNV impacting any gene, and a core set of phenotypic measures. Statistically significant associations between deletions in differentially BE genes were found for family history of mental illness (decreased prevalence of all CNVs and deletions, unadjusted and adjusted) and for paternal age (increase in deletions only, unadjusted, among those with later ages at birth of patient). The strong effect of a lack of a family history on BE genes suggests that CNVs may comprise one pathway to schizophrenia, whereas a positive family history could index other genetic mechanisms that increase schizophrenia vulnerability. To our knowledge, this is the first investigation of the association between genome-wide CNVs and risk factors and sub-phenotypic features of schizophrenia beyond cognitive function.

Review of statistical methodologies for the detection of parent-of-origin effects in family trio genome-wide association data with binary disease traits

The detection of parent-of-origin effects aims to identify whether the functionality of alleles, and in turn associated phenotypic traits, depends on the parental origin of the alleles. Different parent-of-origin effects have been identified through a variety of mechanisms and a number of statistical methodologies for their detection have been proposed, in particular for genome-wide association studies (GWAS). GWAS have had limited success in explaining the heritability of many complex disorders and traits, but successful identification of parent-of-origin effects using trio (mother, father and offspring) GWAS may help shed light on this missing heritability. However, it is important to choose the most appropriate parent-of-origin test or methodology, given knowledge of the phenotype, amount of available data and the type of parent-of-origin effect(s) being considered. This review brings together the parent-of-origin detection methodologies available, comparing them in terms of power and type I error for a number of different simulated data scenarios, and finally offering guidance as to the most appropriate choice for the different scenarios.

No evidence that runs of homozygosity are associated with schizophrenia in an Irish genome-wide association dataset

Runs of homozygosity (ROH), regions of the genome containing many consecutive homozygous SNPs, may represent two copies of a haplotype inherited from a common ancestor. A rare variant on this haplotype could thus be present in a homozygous and potentially recessive state. To detect rare risk variants for schizophrenia, we performed an ROH analysis in a homogeneous Irish genome wide association study (GWAS) dataset consisting of 1606 cases and 1794 controls. There was no genome-wide excess of ROH in cases compared to controls (p=0.7986). No consensus ROH at individual loci showed association with schizophrenia after genome-wide correction.

Individual common variants exert weak effects on the risk for autism spectrum disorders

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.

Genetic classification of populations using supervised learning

There are many instances in genetics in which we wish to determine whether two candidate populations are distinguishable on the basis of their genetic structure. Examples include populations which are geographically separated, case–control studies and quality control (when participants in a study have been genotyped at different laboratories). This latter application is of particular importance in the era of large scale genome wide association studies, when collections of individuals genotyped at different locations are being merged to provide increased power. The traditional method for detecting structure within a population is some form of exploratory technique such as principal components analysis. Such methods, which do not utilise our prior knowledge of the membership of the candidate populations. are termed unsupervised. Supervised methods, on the other hand are able to utilise this prior knowledge when it is available.

In this paper we demonstrate that in such cases modern supervised approaches are a more appropriate tool for detecting genetic differences between populations. We apply two such methods, (neural networks and support vector machines) to the classification of three populations (two from Scotland and one from Bulgaria). The sensitivity exhibited by both these methods is considerably higher than that attained by principal components analysis and in fact comfortably exceeds a recently conjectured theoretical limit on the sensitivity of unsupervised methods. In particular, our methods can distinguish between the two Scottish populations, where principal components analysis cannot. We suggest, on the basis of our results that a supervised learning approach should be the method of choice when classifying individuals into pre-defined populations, particularly in quality control for large scale genome wide association studies.

Exploration of empirical Bayes hierarchical modeling for the analysis of genome-wide association study data

In the analysis of genome-wide association (GWA) data, the aim is to detect statistical associations between single nucleotide polymorphisms (SNPs) and the disease or trait of interest. These SNPs, or the particular regions of the genome they implicate, are then considered for further study. We demonstrate through a comprehensive simulation study that the inclusion of additional, biologically relevant information through a 2-level empirical Bayes hierachical model framework offers a more robust method of detecting associated SNPs. The empirical Bayes approach is an objective means of analyzing the data without the need for the setting of subjective parameter estimates. This framework gives more stable estimates of effects through a reduction of the variability in the usual effect estimates. We also demonstrate the consequences of including additional information that is not informative and examine power and false-positive rates. We apply the methodology to a number of genome-wide association (GWA) data sets with the inclusion of additional biological information. Our results agree with previous findings and in the case of one data set (Crohn's disease) suggest an additional region of interest.

A genome-wide scan for common alleles affecting risk for autism

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10⁻⁸. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10⁻⁸ threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.

Functional impact of global rare copy number variation in autism spectrum disorders

The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviours. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability. Although ASDs are known to be highly heritable ( approximately 90%), the underlying genetic determinants are still largely unknown. Here we analysed the genome-wide characteristics of rare (<1% frequency) copy number variation in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic copy number variants (CNVs) (1.19 fold, P = 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P = 3.4 x 10(-4)). Among the CNVs there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes such as SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53-PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene sets involved in cellular proliferation, projection and motility, and GTPase/Ras signalling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways.

The SNP ratio test: pathway analysis of genome-wide association datasets

We present a tool that assesses the enrichment of significant associations from genome-wide association studies (GWAS) in a pathway context. The SNP ratio test (SRT) compares the proportion of significant to all SNPs within genes that are part of a pathway and computes an empirical P-value based on comparisons to ratios in datasets where the assignment of case/control status has been randomized. We applied the SRT to a Parkinson's disease GWAS dataset, using the KEGG database, revealing significance for Parkinson's disease and related pathways.

AVAILABILITY

https://sourceforge.net/projects/snpratiotest/

Reconstruction of transcriptional dynamics from gene reporter data using differential equations

MOTIVATION

Promoter-driven reporter genes, notably luciferase and green fluorescent protein, provide a tool for the generation of a vast array of time-course data sets from living cells and organisms. The aim of this study is to introduce a modeling framework based on stochastic differential equations (SDEs) and ordinary differential equations (ODEs) that addresses the problem of reconstructing transcription time-course profiles and associated degradation rates. The dynamical model is embedded into a Bayesian framework and inference is performed using Markov chain Monte Carlo algorithms.

RESULTS

We present three case studies where the methodology is used to reconstruct unobserved transcription profiles and to estimate associated degradation rates. We discuss advantages and limits of fitting either SDEs ODEs and address the problem of parameter identifiability when model variables are unobserved. We also suggest functional forms, such as on/off switches and stimulus response functions to model transcriptional dynamics and present results of fitting these to experimental data.

Bayesian inference for dynamic transcriptional regulation; the Hes1 system as a case study

MOTIVATION

In this study, we address the problem of estimating the parameters of regulatory networks and provide the first application of Markov chain Monte Carlo (MCMC) methods to experimental data. As a case study, we consider a stochastic model of the Hes1 system expressed in terms of stochastic differential equations (SDEs) to which rigorous likelihood methods of inference can be applied. When fitting continuous-time stochastic models to discretely observed time series the lengths of the sampling intervals are important, and much of our study addresses the problem when the data are sparse.

RESULTS

We estimate the parameters of an autoregulatory network providing results both for simulated and real experimental data from the Hes1 system. We develop an estimation algorithm using MCMC techniques which are flexible enough to allow for the imputation of latent data on a finer time scale and the presence of prior information about parameters which may be informed from other experiments as well as additional measurement error.

Neuropsychological presentation of Ganser symptoms

We describe a patient with memory complaints whose history of head injury, polysubstance abuse and positive neurological findings suggested the presence of dementia. Neuropsychological testing revealed inconsistent performance plus multiple verbal and visuospatial approximate answers leading to the diagnosis of a Ganser episode. This case illustrates the importance of neuropsychological assessment in diagnosing Ganser symptoms and in differentiating this disorder from organic conditions and malingering.