A Pilot Quantitative Evaluation of Early Life Language Development in Fragile X Syndrome

Language delay and communication deficits are a core characteristic of the fragile X syndrome (FXS) phenotype. To date, the literature examining early language development in FXS is limited potentially due to barriers in language assessment in very young children. The present study is one of the first to examine early language development through vocal production and the language learning environment in infants and toddlers with FXS utilizing an automated vocal analysis system. Child vocalizations, conversational turns, and adult word counts in the home environment were collected and analyzed in a group of nine infants and toddlers with FXS and compared to a typically developing (TD) normative sample. Results suggest infants and toddlers with FXS are exhibiting deficits in their early language skills when compared to their chronological expectations. Despite this, when accounting for overall developmental level, their early language skills appear to be on track. Additionally, FXS caregivers utilize less vocalizations around infants and toddlers with FXS; however, additional research is needed to understand the true gap between FXS caregivers and TD caregivers. These findings provide preliminary information about the early language learning environment and support for the feasibility of utilizing an automated vocal analysis system within the FXS population that could ease data collection and further our understanding of the emergence of language development

Examining Sustained Attention in Child-Parent Interaction: A Comparative Studyof Typically Developing Children and Children with Autism Spectrum Disorder

Sustained attention (SA) is a critical skill in which a child is able tomaintain visual attention to an object or stimulus. The current studyemploys head-mounted eye trackers to study the cognitive processesunderlying SA by analyzing micro-level behaviors during parent-child social interactions in both typically and atypically developingchildren. Specifically, we examined the role of parent look, parenttouch, and child touch on SA duration. Results show that parent lookequally influences SA in both groups, while parent touch is morecritical for SA for TD children and the child’s own touching is morecritical for SA in children with autism spectrum disorder (ASD).Implications of different pathways to maintain SA between typicallydeveloping children and children with ASD are discussed

The Relationship between Expressive Language Sampling and Clinical Measures in Fragile X Syndrome and Typical Development

Language impairment is a core difficulty in fragile X syndrome (FXS), and yet standardized measures lack the sensitivity to assess developmental changes in the nature of these impairments. Expressive Language Sampling Narrative (ELS-N) has emerged as a promising new measure with research demonstrating its usefulness in a wide range of ages in developmental disabilities and typical development. We examined ELS-N results in FXS and age-matched typically developing (TD) controls along with cognitive, adaptive, and clinical measures. We found the groups differed significantly on all ELS-N variables. Cognitive abilities were related to lexical diversity, syntactic complexity, and unintelligibility for the FXS group, but only verbal abilities were related to syntactic complexity in TD. Autism spectrum disorder (ASD) symptomatology was related to less intelligibility in speech. Measures of hyperactivity were related to increased talkativeness and unintelligibility. In addition, FXS males in comparison to FXS females were more impaired in cognitive ability, ASD symptoms, hyperactivity, and anxiety. This study extends the previous ELS research, supporting its use in FXS research as a measure to characterize language abilities. It also demonstrates the relationships between ELS-N variables and measures of cognitive, adaptive, ASD symptoms, and clinical symptoms

The Relationship between Expressive Language Sampling and Clinical Measures in Fragile X Syndrome and Typical Development.

Language impairment is a core difficulty in fragile X syndrome (FXS), and yet standardized measures lack the sensitivity to assess developmental changes in the nature of these impairments. Expressive Language Sampling Narrative (ELS-N) has emerged as a promising new measure with research demonstrating its usefulness in a wide range of ages in developmental disabilities and typical development. We examined ELS-N results in FXS and age-matched typically developing (TD) controls along with cognitive, adaptive, and clinical measures. We found the groups differed significantly on all ELS-N variables. Cognitive abilities were related to lexical diversity, syntactic complexity, and unintelligibility for the FXS group, but only verbal abilities were related to syntactic complexity in TD. Autism spectrum disorder (ASD) symptomatology was related to less intelligibility in speech. Measures of hyperactivity were related to increased talkativeness and unintelligibility. In addition, FXS males in comparison to FXS females were more impaired in cognitive ability, ASD symptoms, hyperactivity, and anxiety. This study extends the previous ELS research, supporting its use in FXS research as a measure to characterize language abilities. It also demonstrates the relationships between ELS-N variables and measures of cognitive, adaptive, ASD symptoms, and clinical symptoms

The Relationship between Expressive Language Sampling and Clinical Measures in Fragile X Syndrome and Typical Development.

Language impairment is a core difficulty in fragile X syndrome (FXS), and yet standardized measures lack the sensitivity to assess developmental changes in the nature of these impairments. Expressive Language Sampling Narrative (ELS-N) has emerged as a promising new measure with research demonstrating its usefulness in a wide range of ages in developmental disabilities and typical development. We examined ELS-N results in FXS and age-matched typically developing (TD) controls along with cognitive, adaptive, and clinical measures. We found the groups differed significantly on all ELS-N variables. Cognitive abilities were related to lexical diversity, syntactic complexity, and unintelligibility for the FXS group, but only verbal abilities were related to syntactic complexity in TD. Autism spectrum disorder (ASD) symptomatology was related to less intelligibility in speech. Measures of hyperactivity were related to increased talkativeness and unintelligibility. In addition, FXS males in comparison to FXS females were more impaired in cognitive ability, ASD symptoms, hyperactivity, and anxiety. This study extends the previous ELS research, supporting its use in FXS research as a measure to characterize language abilities. It also demonstrates the relationships between ELS-N variables and measures of cognitive, adaptive, ASD symptoms, and clinical symptoms

Differentiating social preference and social anxiety phenotypes in fragile X syndrome using an eye gaze analysis: a pilot study

Abstract Background Fragile X syndrome (FXS) is the leading inherited cause of autism spectrum disorder, but there remains debate regarding the clinical presentation of social deficits in FXS. The aim of this study was to compare individuals with FXS to typically developing controls (TDC) and individuals with idiopathic autism spectrum disorder (ASD) across two social eye tracking paradigms. Methods Individuals with FXS and age- and gender-matched TDC and individuals with idiopathic ASD completed emotional face and social preference eye tracking tasks to evaluate gaze aversion and social interest, respectively. Participants completed a battery of cognitive testing and caregiver-reported measures for neurobehavioral characterization. Results Individuals with FXS exhibited reduced eye and increased mouth gaze to emotional faces compared to TDC. Gaze aversive findings were found to correlate with measures of anxiety, social communication deficits, and behavioral problems. In the social interest task, while individuals with idiopathic ASD showed significantly less social preference, individuals with FXS displayed social preference similar to TDC. Conclusions These findings suggest fragile X syndrome social deficits center on social anxiety without the prominent reduction in social interest associated with autism spectrum disorder. Specifically designed eye tracking techniques clarify the nature of social deficits in fragile X syndrome and may have applications to improve phenotyping and evaluate interventions targeting social functioning impairments

Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method

The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t-test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre-defined brain networks including the default-mode, cingulo-opercular, frontal-parietal, and cerebellum. Thirteen of them are statically significant between ASD and TD groups (two sample t-test p < 0.05) while 19 of them are not. The relationship between the statically significant FCs and the corresponding ASD behavior symptoms is discussed based on the literature and clinician's expert knowledge. Meanwhile, the potential reason of obtaining 19 FCs which are not statistically significant is also provided

Clinic variation in recruitment metrics, patient characteristics and treatment use in a randomized clinical trial of osteoarthritis management

Abstract Background The Patient and PRovider Interventions for Managing Osteoarthritis (OA) in Primary Care (PRIMO) study is one of the first health services trials targeting OA in a multi-site, primary care network. This multi-site approach is important for assessing generalizability of the interventions. These analyses describe heterogeneity in clinic and patient characteristics, as well as recruitment metrics, across PRIMO study clinics. Methods Baseline data were obtained from the PRIMO study, which enrolled n = 537 patients from ten Duke Primary Care practices. The following items were examined across clinics with descriptive statistics: (1) Practice Characteristics, including primary care specialty, numbers and specialties of providers, numbers of patients age 55+, urban/rural location and county poverty level; (2) Recruitment Metrics, including rates of eligibility, refusal and randomization; (3) Participants’ Characteristics, including demographic and clinical data (general and OA-related); and (4) Participants’ Self-Reported OA Treatment Use, including pharmacological and non-pharmacological therapies. Intraclass correlation coefficients (ICCs) were computed for participant characteristics and OA treatment use to describe between-clinic variation. Results Study clinics varied considerably across all measures, with notable differences in numbers of patients age 55+ (1,507-5,400), urban/rural location (ranging from “rural” to “small city”), and proportion of county households below poverty level (12%-26%). Among all medical records reviewed, 19% of patients were initially eligible (10%-31% across clinics), and among these, 17% were randomized into the study (13%-21% across clinics). There was considerable between-clinic variation, as measured by the ICC (>0.01), for the following patient characteristics and OA treatment use variables: age (means: 60.4-66.1 years), gender (66%-88% female), race (16%-61% non-white), low income status (5%-27%), presence of hip OA (26%-68%), presence both knee and hip OA (23%-61%), physical therapy for knee OA (24%-61%) and hip OA (0%-71%), and use of knee brace with metal supports (0%-18%). Conclusions Although PRIMO study sites were part of one primary care practice network in one health care system, clinic and patient characteristics varied considerably, as did OA treatment use. This heterogeneity illustrates the importance of including multiple, diverse sites in trials for knee and hip OA, to enhance the generalizability and evaluate potential for real-world implementation. Trial registration Clinical Trial Registration Number: NCT 0143510