Rebecca Embacher

Pediatric Associates, Tampa, Florida, United States

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Publications (6)12.8 Total impact

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    ABSTRACT: PTEN is a tumor suppressor associated with an inherited cancer syndrome and an important regulator of ongoing neural connectivity and plasticity. The present study examined molecular and phenotypic characteristics of individuals with germline heterozygous PTEN mutations and autism spectrum disorder (ASD) (PTEN-ASD), with the aim of identifying pathophysiologic markers that specifically associate with PTEN-ASD and that may serve as targets for future treatment trials. PTEN-ASD patients (n=17) were compared with idiopathic (non-PTEN) ASD patients with (macro-ASD, n=16) and without macrocephaly (normo-ASD, n=38) and healthy controls (n=14). Group differences were evaluated for PTEN pathway protein expression levels, global and regional structural brain volumes and cortical thickness measures, neurocognition and adaptive behavior. RNA expression patterns and brain characteristics of a murine model of Pten mislocalization were used to further evaluate abnormalities observed in human PTEN-ASD patients. PTEN-ASD had a high proportion of missense mutations and showed reduced PTEN protein levels. Compared with the other groups, prominent white-matter and cognitive abnormalities were specifically associated with PTEN-ASD patients, with strong reductions in processing speed and working memory. White-matter abnormalities mediated the relationship between PTEN protein reductions and reduced cognitive ability. The Pten(m3m4) murine model had differential expression of genes related to myelination and increased corpus callosum. Processing speed and working memory deficits and white-matter abnormalities may serve as useful features that signal clinicians that PTEN is etiologic and prompting referral to genetic professionals for gene testing, genetic counseling and cancer risk management; and could reveal treatment targets in trials of treatments for PTEN-ASD.Molecular Psychiatry advance online publication, 7 October 2014; doi:10.1038/mp.2014.125.
    Molecular psychiatry. 10/2014;
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    ABSTRACT: Background: Quality of life (QoL) measures are important intervention and evaluation outcome factors when providing services to individuals with disabilities. Psychosocial QoL is particularly important for caregivers and families of individuals with autism and other developmental disabilities. Most of the existing QoL measures are geared toward physical illnesses or specific developmental conditions. There is a strong need for a measure that is applicable to a range of neurodevelopmental disorders. The Child and Family Quality of Life (CFQL) measure was developed to evaluate psychosocial QoL in neurodevelopmental disorder populations. Objectives: The primary aim of this study was to psychometrically evaluate the CFQL to ensure high reliability of measurement. A secondary objective was to investigate differences in quality of life between children diagnosed with an Autism Spectrum Disorder (ASD) versus children with other developmental disabilities (non-ASD). Methods: Caregivers of 212 individuals (ages 1-7) referred for concern of ASD completed the Child and Family Quality of Life (CFQL) instrument immediately before the first diagnostic assessment visit. The CFQL includes seven scales designed to measure different aspects of child and family QoL: child, family, caregiver, partner relationship, external support, financial, and coping. Scales were designed to be brief, easy-to-complete, and to generate specific clinical actions for scores suggestive of QoL impairment. Average item scores per scale range from 1-5, with scores ≤2 indicating low quality of life. Statistical analyses used to psychometrically evaluate the CFQL included: factor analyses to determine instrument structure, internal consistency reliability, and item response theory-derived reliability estimates across each scale’s latent trait. Group comparisons (ASD vs. non-ASD) across CFQL scales examined whether QoL differed between ASD and non-ASD cases. Results: Factor analyses identified six distinct, positively correlated, factors. Each of the original seven scales comprised a separate factor, with the exception that family and caregiver quality of life items had very high relationships and merged into a single factor in this young sample. Internal consistency reliability was good to excellent for these 4-5 item scales (α=.77-.97), with the exception of marginal reliability for coping (α=.67). Item response theory analyses demonstrated adequate to excellent measurement in the middle of each latent trait from 2SD to +2SD (Reliability >.50), with adequate measurement down to -3SD (low QoL) for some scales. CFQL score distributions suggested highly variable QoL, with a non-trivial proportion of caregivers reporting low child, family, caregiver, and financial QoL (6.1% to 22.2% across scales) immediately prior to the diagnostic evaluation. Lastly, group comparisons found that caregivers of children with ASD reported significantly lower family quality of life (t(210)=2.15, p=.033; Cohen’s d=.30) relative to caregivers of non-ASD children. Non-significant trends were also noted for child (p=.060), caregiver (p=.095), and partner relationship (p=.057). Conclusions: Consistent with previous literature, a significant proportion of families affected by neurodevelopmental disorders report psychosocial QoL disturbance. Interventions are needed that address family QoL very soon after ASD diagnosis. The CFQL appears to be a useful clinical tool at the diagnostic stage for identifying QoL disruptions and developing clinical actions.
    2014 International Meeting for Autism Research; 05/2014
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    ABSTRACT: Demographic and clinical factors may influence assessment of autism symptoms. This study evaluated these correlates and also examined whether social communication and interaction and restricted/repetitive behavior provided unique prediction of autism spectrum disorder diagnosis. We analyzed data from 7352 siblings included in the Interactive Autism Network registry. Social communication and interaction and restricted/repetitive behavior symptoms were obtained using caregiver-reports on the Social Responsiveness Scale. Demographic and clinical correlates were covariates in regression models predicting social communication and interaction and restricted/repetitive behavior symptoms. Logistic regression and receiver operating characteristic curve analyses evaluated the incremental validity of social communication and interaction and restricted/repetitive behavior domains over and above global autism symptoms. Autism spectrum disorder diagnosis was the strongest correlate of caregiver-reported social communication and interaction and restricted/repetitive behavior symptoms. The presence of comorbid diagnoses also increased symptom levels. Social communication and interaction and restricted/repetitive behavior symptoms provided significant, but modest, incremental validity in predicting diagnosis beyond global autism symptoms. These findings suggest that autism spectrum disorder diagnosis is by far the largest determinant of quantitatively measured autism symptoms. Externalizing (attention deficit hyperactivity disorder) and internalizing (anxiety) behavior, low cognitive ability, and demographic factors may confound caregiver-report of autism symptoms, potentially necessitating a continuous norming approach to the revision of symptom measures. Social communication and interaction and restricted/repetitive behavior symptoms may provide incremental validity in the diagnosis of autism spectrum disorder.
    Autism 10/2013; · 2.27 Impact Factor
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    ABSTRACT: Unlike some other childhood neurodevelopmental disorders, no diagnostic biochemical marker has been identified in all individuals with an autism spectrum disorder (ASD). This deficit likely results from genetic heterogeneity among the population. Therefore, we evaluated a subset of individuals with ASDs, specifically, individuals with or without macrocephaly in the presence or absence of PTEN mutations. We sought to determine if amino or organic acid markers could be used to identify individuals with ASDs with or without macrocephaly in the presence or absence of PTEN mutations, and to establish the degree of macrocephaly in individuals with ASDs and PTEN mutation. Urine, blood and occipital-frontal circumference (OFC) measurements were collected from 69 individuals meeting DSM-IV-TR criteria. Urine and plasma samples were subjected to amino and organic acid analyses. PTEN was Sanger-sequenced from germline genomic DNA. Germline PTEN mutations were identified in 27% (6/22) of the macrocephalic ASD population. All six PTEN mutation-positive individuals were macrocephalic with average OFC+4.35 standard deviations (SDs) above the mean. No common biochemical abnormalities were identified in macrocephalic ASD individuals with or without PTEN mutations. In contrast, among the collective ASD population, elevation of urine aspartic acid (87%; 54/62), plasma taurine (69%; 46/67) and reduction of plasma cystine (72%; 46/64) were observed. PTEN sequencing should be carried out for all individuals with ASDs and macrocephaly with OFC ≥2SDs above the mean. A proportion of individuals with ASDs may have an underlying disorder in sulfur amino acid metabolism.European Journal of Human Genetics advance online publication, 22 May 2013; doi:10.1038/ejhg.2013.114.
    European journal of human genetics: EJHG 05/2013; · 3.56 Impact Factor
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    ABSTRACT: The primary aim of the present study was to evaluate the validity of proposed DSM-5 criteria for autism spectrum disorder (ASD). We analyzed symptoms from 14,744 siblings (8,911 ASD and 5,863 non-ASD) included in a national registry, the Interactive Autism Network. Youth 2 through 18 years of age were included if at least one child in the family was diagnosed with ASD. Caregivers reported symptoms using the Social Responsiveness Scale and the Social Communication Questionnaire. The structure of autism symptoms was examined using latent variable models that included categories, dimensions, or hybrid models specifying categories and subdimensions. Diagnostic efficiency statistics evaluated the proposed DSM-5 algorithm in identifying ASD. A hybrid model that included both a category (ASD versus non-ASD) and two symptom dimensions (social communication/interaction and restricted/repetitive behaviors) was more parsimonious than all other models and replicated across measures and subsamples. Empirical classifications from this hybrid model closely mirrored clinical ASD diagnoses (90% overlap), implying a broad ASD category distinct from non-ASD. DSM-5 criteria had superior specificity relative to DSM-IV-TR criteria (0.97 versus 0.86); however sensitivity was lower (0.81 versus 0.95). Relaxing DSM-5 criteria by requiring one less symptom criterion increased sensitivity (0.93 versus 0.81), with minimal reduction in specificity (0.95 versus 0.97). Results supported the validity of proposed DSM-5 criteria for ASD as provided in Phase I Field Trials criteria. Increased specificity of DSM-5 relative to DSM-IV-TR may reduce false positive diagnoses, a particularly relevant consideration for low base rate clinical settings. Phase II testing of DSM-5 should consider a relaxed algorithm, without which as many as 12% of ASD-affected individuals, particularly females, will be missed. Relaxed DSM-5 criteria may improve identification of ASD, decreasing societal costs through appropriate early diagnosis and maximizing intervention resources.
    Journal of the American Academy of Child and Adolescent Psychiatry 01/2012; 51(1):28-40.e3. · 6.97 Impact Factor
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    ABSTRACT: Background: Our group has recently found that many cases of autism spectrum disorders (ASDs) represent a category, qualitatively distinct from typical (non-autism) behavior in clinically ascertained samples (Frazier et. al., in press). The next question concerns whether a broad autism category is composed of sub-categories or is best characterized as a dimension of symptom severity when only autism-affected youth are examined. A recent study addressing this question identified unique sub-categories based upon dysmorphology/head circumference, social communication, and verbal/non-verbal ability scores (Ingram et al., 2008). However, interpretation of these findings is complicated by the aggregation of two different samples, a design feature which may bias toward category identification. Objectives: The present study examined whether autism symptoms would identify sub-categories or a dimension of symptom severity, consistent with the notion of an autism spectrum. This distinction is relevant to future DSM nosology, screening and diagnosis, genetic and neurobiological study design, and identification of differential treatment effects. Methods: Data were obtained from the Interactive Autism Network (IAN) and Autism Genetic Resource Exchange (AGRE) samples and analyzed separately to determine whether results replicate across samples and indicator sets. IAN preferentially recruits families with at least one affected child who has been diagnosed with an ASD. In the IAN sample, caregivers reported autism symptoms using the Social Communication Questionnaire (SCQ) and the Social Responsiveness Scale (SRS). In the AGRE sample, parents were interviewed using the Autism Diagnostic Interview Revised (ADI-R). Autism symptom indicator sets were derived from each measure in each sample. Taxometric and latent variable models evaluated whether 1-group (dimensional) or 2-group (categorical) models fit the data better across indicator sets, demographic sub-samples, and IAN/AGRE samples. These models are blind to diagnostic status and thus provide an empirical test of whether sub-categories or a dimension best describe the data. Results: In the IAN sample, 6875 and 2575 autism-affected participants had SCQ and SRS data, respectively. In the AGRE sample, 889 autism-affected individuals had ADI-R data. Results indicated that dimensional models fit the data better than categorical models. This was true across all taxometric and latent variable procedures, indicator sets, demographic sub-samples, and IAN/AGRE samples. Conclusions: Previously, our group found that ASDs are best conceptualized as a category distinct from typical behavior. The present findings suggest that this broad category includes a continuum of symptom severity. Together, these findings suggest that ASDs may be conceptualized as a single, discrete entity that is distinct from typical behavior but that shows large variation in symptom severity. This conclusion does not rule out the possibility of autism sub-groups. However, the results imply that indicators beyond autism symptoms, such as cognitive or biological indicators, will be needed to identify autism sub-groupings.
    International Meeting for Autism Research 2010; 05/2010