TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Mach Bands: multi-scale spatial filtering and co-operative coding of edges and bars

Perception of Mach bands may be explained by spatial filtering ('lateral inhibition') that can be approximated by 2nd derivative computation, and several alternative models have been proposed. To distinguish between them, we used a novel set of ‘generalised Gaussian’ images, in which the sharp ramp-plateau junction of the Mach ramp was replaced by smoother transitions. The images ranged from a slightly blurred Mach ramp to a Gaussian edge and beyond, and also included a sine-wave edge. The probability of seeing Mach Bands increased with the (relative) sharpness of the junction, but was largely independent of absolute spatial scale. These data did not fit the predictions of MIRAGE, nor 2nd derivative computation at a single fine scale. In experiment 2, observers used a cursor to mark features on the same set of images. Data on perceived position of Mach bands did not support the local energy model. Perceived width of Mach bands was poorly explained by a single-scale edge detection model, despite its previous success with Mach edges (Wallis & Georgeson, 2009, Vision Research, 49, 1886-1893). A more successful model used separate (odd and even) scale-space filtering for edges and bars, local peak detection to find candidate features, and the MAX operator to compare odd- and even-filter response maps (Georgeson, VSS 2006, Journal of Vision 6(6), 191a). Mach bands are seen when there is a local peak in the even-filter (bar) response map, AND that peak value exceeds corresponding responses in the odd-filter (edge) maps.

A new candidate locus for bilateral perisylvian polymicrogyria mapped on chromosome Xq27

Polymicrogyria (PMG) is characterized by an excessive number of small and prominent brain gyri, separated by shallow sulci. Bilateral perisylvian polymicrogyria (BPP) is the most common form of PMG. Clinical signs include pseudobulbar paresis, mental retardation, and epilepsy. Familial forms of BPP have been described and a candidate locus was previously mapped to chromosome Xq28, distal do marker DXS8103. The objective of this study was to perform linkage analysis in one family segregating BPP. A total of 15 individuals, including 8 affected patients with BPP were evaluated. Family members were examined by a neurologist and subjected to magnetic resonance imaging scans. Individuals were genotyped for 18 microsatellite markers, flanking a 42.3 cM interval on ch Xq27-q28. Two-point and multipoint linkage analysis was performed using the LINKAGE package and haplotype reconstruction was performed by GENEHUNTER software. Our results showed a wide spectrum of clinical manifestations in affected individuals with BPP, ranging from normal to mild neurological abnormalities. Two-point linkage analysis yield a Zmax=2.06 at theta=0.00 for markers DXS1205 and DXS1227. Multipoint lod-scores indicate a candidate interval of 13 cM between markers DSXS1205 and DXS8043, on ch Xq27.2-Xq27.3. These results point to a new locus for BPP in a more centromeric location than previously reported. (C) 2008 Wiley-Liss, Inc.

Global localization with non-quantized local image features

In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.

Ankylosing spondylitis: genomic and functional characterization of candidate genes and their repercussion in clinical practice

RESUMO: Introdução: A espondilite anquilosante (EA) é uma doença inflamatória crónica caracterizada pela inflamação das articulações sacroilíacas e da coluna. A anquilose progressiva motiva uma deterioração gradual da função física e da qualidade de vida. O diagnóstico e o tratamento precoces podem contribuir para um melhor prognóstico. Neste contexto, a identificação de biomarcadores, assume-se como sendo muito útil para a prática clínica e representa hoje um grande desafio para a comunidade científica. Objetivos: Este estudo teve como objetivos: 1 - caracterizar a EA em Portugal; 2 - investigar possíveis associações entre genes, MHC e não-MHC, com a suscetibilidade e as características fenotípicas da EA; 3 - identificar genes candidatos associados a EA através da tecnologia de microarray. Material e Métodos: Foram recrutados doentes com EA, de acordo com os critérios modificados de Nova Iorque, nas consultas de Reumatologia dos diferentes hospitais participantes. Colecionaram-se dados demográficos, clínicos e radiológicos e colhidas amostras de sangue periférico. Selecionaram-se de forma aleatória, doentes HLA-B27 positivos, os quais foram tipados em termos de HLA classe I e II por PCR-rSSOP. Os haplótipos HLA estendidos foram estimados pelo algoritmo Expectation Maximization com recurso ao software Arlequin v3.11. As variantes alélicas dos genes IL23R, ERAP1 e ANKH foram estudadas através de ensaios de discriminação alélica TaqMan. A análise de associação foi realizada utilizando testes da Cochrane-Armitage e de regressão linear, tal como implementado pelo PLINK, para variáveis qualitativas e quantitativas, respetivamente. O estudo de expressão génica foi realizado por Illumina HT-12 Whole-Genome Expression BeadChips. Os genes candidatos foram validados usando qPCR-based TaqMan Low Density Arrays (TLDAs). Resultados: Foram incluídos 369 doentes (62,3% do sexo masculino, com idade média de 45,4 ± 13,2 anos, duração média da doença de 11,4 ± 10,5 anos). No momento da avaliação, 49,9% tinham doença axial, 2,4% periférica, 40,9% mista e 7,1% entesopática. A uveíte anterior aguda (33,6%) foi a manifestação extra-articular mais comum. Foram positivos para o HLA-B27, 80,3% dos doentes. Os haplótipo A*02/B*27/Cw*02/DRB1*01/DQB1*05 parece conferir suscetibilidade para a EA, e o A*02/B*27/Cw*01/DRB1*08/DQB1*04 parece conferir proteção em termos de atividade, repercussão funcional e radiológica da doença. Três variantes (2 para IL23R e 1 para ERAP1) mostraram significativa associação com a doença, confirmando a associação destes genes com a EA na população Portuguesa. O mesmo não se verificou com as variantes estudadas do ANKH. Não se verificou associação entre as variantes génicas não-MHC e as manifestações clínicas da EA. Foi identificado um perfil de expressão génica para a EA, tendo sido validados catorze genes - alguns têm um papel bem documentado em termos de inflamação, outros no metabolismo da cartilagem e do osso. Conclusões: Foi estabelecido um perfil demográfico e clínico dos doentes com EA em Portugal. A identificação de variantes génicas e de um perfil de expressão contribuem para uma melhor compreensão da sua fisiopatologia e podem ser úteis para estabelecer modelos com relevância em termos de diagnóstico, prognóstico e orientação terapêutica dos doentes. -----------ABSTRACT: Background: Ankylosing Spondylitis (AS) is a chronic inflammatory disorder characterized by inflammation in the spine and sacroiliac joints leading to progressive joint ankylosis and in progressive deterioration of physical function and quality of life. An early diagnosis and early therapy may contribute to a better prognosis. The identification of biomarkers would be helpful and represents a great challenge for the scientific community. Objectives: The present study had the following aims: 1- to characterize the pattern of AS in Portuguese patients; 2- to investigate MHC and non-MHC gene associations with susceptibility and phenotypic features of AS and; 3- to identify candidate genes associated with AS by means of whole-genome microarray. Material and Methods: AS was defined in accordance to the modified New York criteria and AS cases were recruited from hospital outcares patient clinics. Demographic and clinical data were recorded and blood samples collected. A random group of HLA-B27 positive patients and controls were selected and typed for HLA class I and II by PCR-rSSOP. The extended HLA haplotypes were estimated by Expectation Maximization Algorithm using Arlequin v3.11 software. Genotyping of IL23R, ERAP1 and ANKH allelic variants was carried out with TaqMan allelic discrimination assays. Association analysis was performed using the Cochrane-Armitage and linear regression tests as implemented in PLINK, for dichotomous and quantitative variables, respectively. Gene expression profile was carried out using Illumina HT-12 Whole-Genome Expression BeadChips and candidate genes were validated using qPCR-based TaqMan Low Density Arrays (TLDAs). Results: A total of 369 patients (62.3% male; mean age 45.4±13.2 years; mean disease duration 11.4±10.5 years), were included. Regarding clinical disease pattern, at the time of assessment, 49.9% had axial disease, 2.4% peripheral disease, 40.9% mixed disease and 7.1% isolated enthesopathic disease. Acute anterior uveitis (33.6%) was the most common extra-articular manifestation. 80.3% of AS patients were HLA-B27 positive. The haplotype A*02/B*27/Cw*02/DRB1*01/DQB1*05 seems to confer susceptibility to AS, whereas A*02/B*27/Cw*01/DRB1*08/DQB1*04 seems to provide protection in terms of disease activity, functional and radiological repercussion. Three markers (two for IL23R and one for ERAP1) showed significant single-locus disease associations. Association of these genes with AS in the Portuguese population was confirmed, whereas ANKH markers studied did not show an association with AS. No association was seen between non-MHC genes and clinical manifestations of AS. A gene expression signature for AS was established; among the fourteen validated genes, a number of them have a well-documented inflammatory role or in modulation of cartilage and bone metabolism. Conclusions: A demographic and clinical profile of patients with AS in Portugal was established. Identification of genetic variants of target genes as well as gene expression signatures could provide a better understanding of AS pathophysiology and could be useful to establish models with relevance in terms of susceptibility, prognosis, and potential therapeutic guidance.

Genotypic features of lentivirus transgenic mice.

Lentivector-mediated transgenesis is increasingly used, whether for basic studies as an alternative to pronuclear injection of naked DNA or to test candidate gene therapy vectors. In an effort to characterize the genetic features of this approach, we first measured the frequency of germ line transmission of individual proviruses established by infection of fertilized mouse oocytes. Seventy integrants from 11 founder (G0) mice were passed to 111 first generation (G1) pups, for a total of 255 events corresponding to an average rate of transmission of 44%. This implies that integration had most often occurred at the one- or two-cell stage and that the degree of genotypic mosaicism in G0 mice obtained through this approach is generally minimal. Transmission analysis of eight individual proviruses in 13 G2 mice obtained by a G0-G1 cross revealed only 8% of proviral homozygosity, significantly below the 25% expected from purely Mendelian transmission, suggesting counter-selection due to interference with the functions of targeted loci. Mapping of 239 proviral integration sites in 49 founder animals revealed that about 60% resided within annotated genes, with a marked tendency for clustering in the middle of the transcribed region, and that integration was not influenced by the transcriptional orientation. Transcript levels of a set of arbitrarily chosen target genes were significantly higher in two-cell embryos than in embryonic stem cells or adult somatic cells, suggesting that, as previously noted in other settings, lentiviral vectors integrate preferentially into regions of the genome that are transcriptionally active or poised for activation.

Spatial analysis of corresponding fingerprint features from match and close non-match populations

The development of statistical models for forensic fingerprint identification purposes has been the subject of increasing research attention in recent years. This can be partly seen as a response to a number of commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. In addition, key forensic identification bodies such as ENFSI [1] and IAI [2] have recently endorsed and acknowledged the potential benefits of using statistical models as an important tool in support of the fingerprint identification process within the ACE-V framework. In this paper, we introduce a new Likelihood Ratio (LR) model based on Support Vector Machines (SVMs) trained with features discovered via morphometric and spatial analyses of corresponding minutiae configurations for both match and close non-match populations often found in AFIS candidate lists. Computed LR values are derived from a probabilistic framework based on SVMs that discover the intrinsic spatial differences of match and close non-match populations. Lastly, experimentation performed on a set of over 120,000 publicly available fingerprint images (mostly sourced from the National Institute of Standards and Technology (NIST) datasets) and a distortion set of approximately 40,000 images, is presented, illustrating that the proposed LR model is reliably guiding towards the right proposition in the identification assessment of match and close non-match populations. Results further indicate that the proposed model is a promising tool for fingerprint practitioners to use for analysing the spatial consistency of corresponding minutiae configurations.

A recombinant rubella virus E1 glycoprotein as a rubella vaccine candidate.

A recombinant rubella virus E1 (rE1) glycoprotein was produced and some of its chemical and immunological features were characterized. Two animal models were then used to establish that the rE1 glycoprotein and rubella virus particles shared antigenic and immunogenic properties. In the first one, sera from rE1 glycoprotein-immunized BALB/c mice neutralized in vitro rubella virus infection. In the second model, severe combined immune deficient (SCID) mice implanted with tonsil fragments from rubella immune donors and immunized with rE1 glycoprotein produced human anti-rubella virus antibodies. Altogether, these results showed that immunization with rE1 glycoprotein elicited neutralizing anti-rubella virus antibodies. This study thus indicated that the rE1 glycoprotein could constitute a non-replicating rubella vaccine.

Identification of Methylated Genes Associated with Aggressive Clinicopathological Features in Mantle Cell Lymphoma

Background: Mantle cell lymphoma (MCL) is genetically characterized by the t(11;14)(q13;q32) translocation and a high number of secondary chromosomal alterations. The contribution of DNA methylation to MCL lymphomagenesis is not well known. We sought to identify epigenetically silenced genes in these tumours that might have clinical relevance. Methodology/Principal Findings: To identify potential methylated genes in MCL we initially investigated seven MCL cell lines treated with epigenetic drugs and gene expression microarray profiling. The methylation status of selected candidate genes was validated by a quantitative assay and subsequently analyzed in a series of primary MCL (n=38). After pharmacological reversion we identified 252 potentially methylated genes. The methylation analysis of a subset of these genes (n=25) in the MCL cell lines and normal B lymphocytes confirmed that 80% of them were methylated in the cell lines but not in normal lymphocytes. The subsequent analysis in primary MCL identified five genes (SOX9,HOXA9,AHR,NR2F2 ,and ROBO1) frequently methylated in these tumours. The gene methylation events tended to occur in the same primary neoplasms and correlated with higher proliferation, increased number of chromosomal abnormalities, and shorter survival of the patients. Conclusions: We have identified a set of genes whose methylation degree and gene expression levels correlate with aggressive clinicopathological features of MCL. Our findings also suggest that a subset of MCL might show a CpG island methylator phenotype (CIMP) that may influence the behaviour of the tumours.

Identification of Methylated Genes Associated with Aggressive Clinicopathological Features in Mantle Cell Lymphoma

Background: Mantle cell lymphoma (MCL) is genetically characterized by the t(11;14)(q13;q32) translocation and a high number of secondary chromosomal alterations. The contribution of DNA methylation to MCL lymphomagenesis is not well known. We sought to identify epigenetically silenced genes in these tumours that might have clinical relevance. Methodology/Principal Findings: To identify potential methylated genes in MCL we initially investigated seven MCL cell lines treated with epigenetic drugs and gene expression microarray profiling. The methylation status of selected candidate genes was validated by a quantitative assay and subsequently analyzed in a series of primary MCL (n=38). After pharmacological reversion we identified 252 potentially methylated genes. The methylation analysis of a subset of these genes (n=25) in the MCL cell lines and normal B lymphocytes confirmed that 80% of them were methylated in the cell lines but not in normal lymphocytes. The subsequent analysis in primary MCL identified five genes (SOX9,HOXA9,AHR,NR2F2 ,and ROBO1) frequently methylated in these tumours. The gene methylation events tended to occur in the same primary neoplasms and correlated with higher proliferation, increased number of chromosomal abnormalities, and shorter survival of the patients. Conclusions: We have identified a set of genes whose methylation degree and gene expression levels correlate with aggressive clinicopathological features of MCL. Our findings also suggest that a subset of MCL might show a CpG island methylator phenotype (CIMP) that may influence the behaviour of the tumours.

Candidate counterparts to the soft gamma-ray flare in the direction od LSI+61303

A short duration burst reminiscent of a soft gamma-ray repeater/anomalous X-ray pulsar behaviour was detected in the direction of LS I +61 303 by the Swift satellite. While the association with this well known gamma-ray binary is likely, a different origin cannot be excluded. Aims. We explore the error box of this unexpected flaring event and establish the radio, near-infrared and X-ray sources in our search for any peculiar alternative counterpart. Methods. We carried out a combined analysis of archive Very Large Array radio data of LS I +61 303 sensitive to both compact and extended emission. We also reanalysed previous near infrared observations with the 3.5 m telescope of the Centro Astronómico Hispano Alemán and X-ray observations with the Chandra satellite. Results. Our deep radio maps of the LS I +61 303 environment represent a significant advancement on previous work and 16 compact radio sources in the LS I +61 303 vicinity are detected. For some detections, we also identify near infrared and X-ray counterparts. Extended emission features in the field are also detected and confirmed. The possible connection of some of these sources with the observed flaring event is considered. Based on these data, we are unable to claim a clear association between the Swift-BAT flare and any of the sources reported here. However, this study represents the most sophisticated attempt to determine possible alternative counterparts other than LS I +61 303.

VAP-1 as drug target in inflammation : structural features determining ligand interactions

Vascular adhesion protein-1 (VAP-1), which belongs to the copper amine oxidases (CAOs), is a validated drug target in inflammatory diseases. Inhibition of VAP-1 blocks the leukocyte trafficking to sites of inflammation and alleviates inflammatory reactions. In this study, a novel set of potent pyridazinone inhibitors is presented together with their X-ray structure complexes with VAP-1. The crystal structure of serum VAP-1 (sVAP-1) revealed an imidazole binding site in the active site channel and, analogously, the pyridazinone inhibitors were designed to bind into the channel. This is the first time human VAP-1 has been crystallized with a reversible inhibitor and the structures reveal detailed information of the binding mode on the atomic level. Similarly to some earlier studied inhibitors of human VAP-1, the designed pyridazinone inhibitors bind rodent VAP-1 with a lower affinity than human VAP-1. Therefore, we made homology models of rodent VAP-1 and compared human and rodent enzymes to determine differences that might affect the inhibitor binding. The comparison of the crystal structures of the human VAP-1 and the mouse VAP-1 homology model revealed key differences important for the species specific binding properties. In general, the channel in mouse VAP-1 is more narrow and polar than the channel in human VAP-1, which is wider and more hydrophobic. The differences are located in the channel leading to the active site, as well as, in the entrance to the active site channel. The information obtained from these studies is of great importance for the development and design of drugs blocking the activity of human VAP-1, as rodents are often used for in vivo testing of candidate drugs. In order to gain more insight into the selective binding properties of the different CAOs in one species a comprehensive evolutionary study of mammalian CAOs was performed. We found that CAOs can be classified into sub-families according to the residues X1 and X2 of the Thr/Ser-X1-X2-Asn-Tyr-Asp active site motif. In the phylogenetic tree, CAOs group into diamine oxidase, retina specific amine oxidase and VAP-1/serum amine oxidase clades based on the residue in the position X2. We also found that VAP-1 and SAO can be further differentiated based on the residue in the position X1. This is the first large-scale comparison of CAO sequences, which explains some of the reasons for the unique substrate specificities within the CAO family.

Evolving features-algorithms knowledge map to support NIDS data intelligence and learning loop architecting – a generalised approach to NIDS pattern feature space knowledge processing

This paper describes a proposed new approach to the Computer Network Security Intrusion Detection Systems (NIDS) application domain knowledge processing focused on a topic map technology-enabled representation of features of the threat pattern space as well as the knowledge of situated efficacy of alternative candidate algorithms for pattern recognition within the NIDS domain. Thus an integrative knowledge representation framework for virtualisation, data intelligence and learning loop architecting in the NIDS domain is described together with specific aspects of its deployment.

Variation in the autism candidate gene GABRB3 modulates tactile sensitivity in typically developing children

Background: Autism spectrum conditions have a strong genetic component. Atypical sensory sensitivities are one of the core but neglected features of autism spectrum conditions. GABRB3 is a well-characterised candidate gene for autism spectrum conditions. In mice, heterozygous Gabrb3 deletion is associated with increased tactile sensitivity. However, no study has examined if tactile sensitivity is associated with GABRB3 genetic variation in humans. To test this, we conducted two pilot genetic association studies in the general population, analysing two phenotypic measures of tactile sensitivity (a parent-report and a behavioural measure) for association with 43 SNPs in GABRB3. Findings: Across both tactile sensitivity measures, three SNPs (rs11636966, rs8023959 and rs2162241) were nominally associated with both phenotypes, providing a measure of internal validation. Parent-report scores were nominally associated with six SNPs (P <0.05). Behaviourally measured tactile sensitivity was nominally associated with 10 SNPs (three after Bonferroni correction). Conclusions: This is the first human study to show an association between GABRB3 variation and tactile sensitivity. This provides support for the evidence from animal models implicating the role of GABRB3 variation in the atypical sensory sensitivity in autism spectrum conditions. Future research is underway to directly test this association in cases of autism spectrum conditions.

A novel microdeletion syndrome at 3q13.31 characterised by developmental delay, postnatal overgrowth, hypoplastic male genitals, and characteristic facial features

Background Congenital deletions affecting 3q11q23 have rarely been reported and only five cases have been molecularly characterised. Genotype. phenotype correlation has been hampered by the variable sizes and breakpoints of the deletions. In this study, 14 novel patients with deletions in 3q11q23 were investigated and compared with 13 previously reported patients. Methods Clinical data were collected from 14 novel patients that had been investigated by high resolution microarray techniques. Molecular investigation and updated clinical information of one cytogenetically previously reported patient were also included. Results The molecular investigation identified deletions in the region 3q12.3q21.3 with different boundaries and variable sizes. The smallest studied deletion was 580 kb, located in 3q13.31. Genotype. phenotype comparison in 24 patients sharing this shortest region of overlapping deletion revealed several common major characteristics including significant developmental delay, muscular hypotonia, a high arched palate, and recognisable facial features including a short philtrum and protruding lips. Abnormal genitalia were found in the majority of males, several having micropenis. Finally, a postnatal growth pattern above the mean was apparent. The 580 kb deleted region includes five RefSeq genes and two of them are strong candidate genes for the developmental delay: DRD3 and ZBTB20. Conclusion A newly recognised 3q13.31 microdeletion syndrome is delineated which is of diagnostic and prognostic value. Furthermore, two genes are suggested to be responsible for the main phenotype.