cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15154/1373363
title: Risk of weight gain for specific antipsychotic drugs: A Bayesian network meta-analysis of individual participant level clinical trial data

description: People with schizophrenia are at considerably higher risk of cardiometabolic morbidity than the general population. Second-generation antipsychotic drugs contribute to that risk partly through their weight gain effects, exacerbating an already high burden of disease. While standard ‘as-randomized’ analyses of clinical trials provide valuable information, they ignore adherence patterns across treatment arms, confounding estimates of realized treatment exposure on outcome. We assess the effect of specific second-generation antipsychotics on weight gain, defined as at least a 7% increase in weight from randomization, using a Bayesian hierarchical model network meta-analysis with individual patient level data. Our data consisted of 14 randomized clinical trials contributing 5923 subjects (mean age = 39 [SD = 12]) assessing various combinations of olanzapine (n = 533), paliperidone (n = 3482), risperidone (n= 540), and placebo (n= 1368). The median time from randomization to dropout or trial completion was 6 weeks (range: 0-60 weeks). The unadjusted probability of weight gain in the placebo group was 4.8% across trials. For each 10g chlorpromazine equivalent dose increase in olanzapine, the odds of weight gain increased by 5.0 (95% Credible Interval: 1.4, 5.3); the effect of risperidone (odds ratio = 1.6 [0.25,9.1]) was estimated with considerable uncertainty but was similar to paliperidone (odds ratio = 1.3 [1.2, 1.5]).
DOI: 10.15154/1375033
title: Early brain development in infants at high risk for autism spectrum disorder

description: Brain enlargement has been observed in children with autism spectrum disorder (ASD), but the timing of this phenomenon, and the relationship between ASD and the appearance of behavioural symptoms, are unknown. Retrospective head circumference and longitudinal brain volume studies of two-year olds followed up at four years of age have provided evidence that increased brain volume may emerge early in development1, 2. Studies of infants at high familial risk of autism can provide insight into the early development of autism and have shown that characteristic social deficits in ASD emerge during the latter part of the first and in the second year of life3, 4. These observations suggest that prospective brain-imaging studies of infants at high familial risk of ASD might identify early postnatal changes in brain volume that occur before an ASD diagnosis. In this prospective neuroimaging study of 106 infants at high familial risk of ASD and 42 low-risk infants, we show that hyperexpansion of the cortical surface area between 6 and 12 months of age precedes brain volume overgrowth observed between 12 and 24 months in 15 high-risk infants who were diagnosed with autism at 24 months. Brain volume overgrowth was linked to the emergence and severity of autistic social deficits. A deep-learning algorithm that primarily uses surface area information from magnetic resonance imaging of the brain of 6–12-month-old individuals predicted the diagnosis of autism in individual high-risk children at 24 months (with a positive predictive value of 81% and a sensitivity of 88%). These findings demonstrate that early brain changes occur during the period in which autistic behaviours are first emerging.
DOI: 10.15154/1375730
title: Neural Correlates of Global and Specific Cognitive Deficits in Schizophrenia

description: Cognitive deficits are a core feature of schizophrenia, but the neural mechanisms that contribute to these characteristics are not fully understood. This study investigated whether volume of the dorsal lateral prefrontal cortex (DLPFC), hippocampus, and white matter were associated with impairment in specific cognitive domains, including executive functioning, working memory, verbal memory, verbal fluency, processing speed, versus global functioning. The multi-site data used in this study was collected from the Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP), and consisted of 206 healthy controls and 247 individuals with either schizophrenia or schizoaffective disorder. The neuroimaging data was segmented based on the Destrieux atlas in FreeSurfer. Linear regression analyses revealed that DLPFC volume was positively associated with executive functioning and processing speed, but not with working memory or verbal memory. Hippocampal volume was positively associated with executive functioning, working memory, and verbal memory, but not with verbal fluency. White matter volume was positively associated with processing speed, but not verbal fluency. Volume of all three brain structures were also associated with global cognitive functioning. However, DLPFC, hippocampal, and white matter volume were significantly associated with executive functioning even when controlling for global cognition, identifying a specific relationship. These findings suggest that volume of the DLPFC, hippocampus, and white matter are associated with both the global cognitive deficit in schizophrenia and with executive functioning, but may not have specific relationships to other cognitive domains over and above the global deficit.
DOI: 10.15154/1376893
title: Combining Gaze and Demographic Feature Descriptors for Autism Classification

description: People with autism suffer from social challenges and communication difficulties, which may prevent them from leading a fruitful and enjoyable life. It is imperative to diagnose and start treatments for autism as early as possible and, in order to do so, accurate methods of identifying the disorder are vital. We propose a novel method for classifying autism through the use of eye gaze and demographic feature descriptors that include a subject’s age and gender. We construct feature descriptors that incorporate the subject’s age and gender, as well as features based on eye gaze data. Using eye gaze information from the National Database for Autism Research, we tested our constructed feature descriptors on three different classifiers; random regression forests, C4.5 decision tree, and PART. Our proposed method for classifying autism resulted in a top classification rate of 96.2%.
DOI: 10.15154/1376898
title: PING Genomics Derived Data

description: The PING Data Resource is the product of a multi-site project involving developmental researchers across the United States including UC San Diego the University of Hawaii UC Los Angeles Childrens Hospital of Los Angeles of the University of Southern California UC Davis Kennedy Krieger Institute of Johns Hopkins University Sackler Institute of Cornell University University of Massachusetts Massachusetts General Hospital at Harvard University and Yale University. The Data Resource includes neurodevelopmental histories, information about developing mental and emotional functions, multimodal brain imaging data, and genotypes for well over 1000 children and adolescents between the ages of 3 and 20.
DOI: 10.15154/1399251
title: How We Transmit Memories to Other Brains: Constructing Shared Neural Representations Via Communication.

description: Humans are able to mentally construct an episode when listening to another person's recollection, even though they themselves did not experience the events. However, it is unknown how strongly the neural patterns elicited by mental construction resemble those found in the brain of the individual who experienced the original events. Using fMRI and a verbal communication task, we traced how neural patterns associated with viewing specific scenes in a movie are encoded, recalled, and then transferred to a group of naïve listeners. By comparing neural patterns across the 3 conditions, we report, for the first time, that event-specific neural patterns observed in the default mode network are shared across the encoding, recall, and construction of the same real-life episode. This study uncovers the intimate correspondences between memory encoding and event construction, and highlights the essential role our common language plays in the process of transmitting one's memories to other brains.
DOI: 10.15154/1400378
title: Amplification of local changes along the timescale processing hierarchy.

description: Small changes in word choice can lead to dramatically different interpretations of narratives. How does the brain accumulate and integrate such local changes to construct unique neural representations for different stories? In this study, we created two distinct narratives by changing only a few words in each sentence (e.g., "he" to "she" or "sobbing" to "laughing") while preserving the grammatical structure across stories. We then measured changes in neural responses between the two stories. We found that differences in neural responses between the two stories gradually increased along the hierarchy of processing timescales. For areas with short integration windows, such as early auditory cortex, the differences in neural responses between the two stories were relatively small. In contrast, in areas with the longest integration windows at the top of the hierarchy, such as the precuneus, temporal parietal junction, and medial frontal cortices, there were large differences in neural responses between stories. Furthermore, this gradual increase in neural differences between the stories was highly correlated with an area's ability to integrate information over time. Amplification of neural differences did not occur when changes in words did not alter the interpretation of the story (e.g., sobbing to "crying"). Our results demonstrate how subtle differences in words are gradually accumulated and amplified along the cortical hierarchy as the brain constructs a narrative over time.
DOI: 10.15154/1405095
title: Gender differences in restricted and repetitive behaviors and interests in autism

description: Background: The female autism phenotype has been defined by differences in core autism spectrum disorder (ASD) symptomology related to reciprocal social communication and restricted and repetitive behaviors and interests (RRBI). Previous research on RRBI in ASD has found that affected boys have increased stereotyped and restricted behaviors compared to girls with ASD (Hiller, Young, & Weber, 2014; Mandy et al., 2012). Other domains of RRBI (i.e., self-injurious, compulsive, and insistence on sameness behaviors), which contribute to DSM-5 diagnosis, are less studied and have not been examined across gender. To date, no studies have examined gender differences using a comprehensive RRBI measure, which spans stereotyped, self-injurious, compulsive, insistence on sameness, and restricted behavior domains. 
Objectives: To investigate whether symptoms of RRBI (i.e., stereotyped, self-injurious, ritualistic, compulsive, insistence on sameness, and restricted behavior), as measured by item-level data on the Repetitive Behavior Scale-Revised (RBS-R), can classify males versus females with ASD.
Methods: Participants included 615 youth with ASD (507 males; 82.4%), between 3 and 18 years of age (M=10.26, SD=4.20), who agreed to share data with the National Database for Autism Research (NDAR). A stepwise discriminant function analysis (DFA) was used to predict the degree RBS-R data could correctly classify gender in a large sample of individuals with ASD. Standardized canonical function coefficients (SCFC) from the DFA represent the contribution of each variable to the discrimination between groups, with greater SCFC indicating greater discrimination. 
Results: DFA results suggest that RBS-R items significantly differentiate girls versus boys with ASD, Wilks’ λ=0.89, χ2=70.79, p&lt;0.001. Of note, gender was classified based on a set of 8 items (see table 1). Interestingly, the items that differentiated boys from girls did not solely consist of higher stereotyped and restricted behavior in boys (as indicated by negative SCFC scores). Half of the items that differentiated gender were higher in females with ASD  (as indicated by positive SCFC scores) and from the self-injurious, compulsive, and insistence on sameness domains. This set of RBS-R items had greater success in correctly classifying boys with ASD (67.90%) than in correctly classifying affected girls (61.00%). 
Conclusions: This study extends findings of gender differences in RRBI for ASD, demonstrating that girls with ASD may demonstrate higher self-injurious, compulsive, and insistence on sameness behavior than affected boys. It is important for future research to disentangle whether these elevated rates of RRBI in girls with ASD are central to the female autism phenotype or an epiphenomenon of the high rates of co-occurring disorders (e.g., anxiety) noted in affected girls.
DOI: 10.15154/1407407
title: Mitochondrial DNA mutations in Autism Spectrum Disorder

description: Mitochondrial dysfunction is frequently observed in Autism Spectrum Disorders (ASD). Thus, variations in the mitochondrial DNA (mtDNA) sequences may contribute to increased ASD risks. In the current study, we evaluated mtDNA variations, including homoplasmy and heteroplasmy, in 903 ASD individuals along with their mothers and non-ASD siblings by using off-target reads from whole-exome sequencing data sets of Simons Foundation Autism Research Initiative (SFARI) Simons Collection available on NDAR. We found that heteroplasmic mutations in ASD individuals were enriched at non-polymorphic mtDNA sites (P = 0.0015) compared to their non-ASD siblings, which were more likely to confer deleterious effects than heteroplasmies at polymorphic mtDNA sites. Accordingly, we observed a ~1.5-fold enrichment of nonsynonymous mutations as well as a ~2.2-fold enrichment of predicted pathogenic mutations (P &lt; 0.003) in ASD individuals compared to their non-ASD siblings. Our genetic findings substantiate pathogenic mtDNA mutations as a potential cause for ASD and synergize with recent work calling attention to their unique metabolic phenotypes for diagnosis and treatment of ASD.
DOI: 10.15154/1410419
title: Different mutational rates and mechanisms in human cells at pre-gastrulation and neurogenesis

description: Somatic mosaicism in the human brain may alter function of individual neurons. We analyzed genomes of single cells from the forebrains of three human fetuses (15 to 21 weeks post-conception) using clonal cell populations. We detected 200-400 single nucleotide variations (SNVs) per cell. SNV patterns resembled those found in cancer cell genomes, indicating a role of background mutagenesis in cancer. SNVs with a frequency of &gt;2% in brain were shared with the spleen, revealing a pre-gastrulation origin. We reconstructed cell lineages for the first five post-zygotic cleavages and calculated a mutation rate of ~1.3 per division per cell. Later in development, during neurogenesis, the mutation spectrum shifted towards oxidative damage and the mutation rate increased. Both neurogenesis and early embryogenesis exhibit drastically more mutagenesis than adulthood.
DOI: 10.15154/1418277
title: Changes in ventromedial prefrontal and insular cortex support the development of metamemory from childhood into adolescence.

description: Metamemory monitoring, or the ability to introspect on the accuracy of one's memories, improves considerably during childhood, but the underlying neural changes and implications for intellectual development are largely unknown. The present study examined whether cortical changes in key brain areas hypothesized to support metacognition contribute to the development of metamemory monitoring from late childhood into early adolescence. Metamemory monitoring was assessed among 7- to 12-y-old children (n = 145) and adults (n = 31). Children returned for up to two additional assessments at 8 to 14 y of age (n = 120) and at 9 to 15 y of age (n = 107) (n = 347 longitudinal scans). Results showed that metamemory monitoring continues to improve from childhood into adolescence. More pronounced cortical thinning in the anterior insula and a greater increase in the thickness of the ventromedial prefrontal cortex over the three assessment points predicted these improvements. Thus, performance benefits are linked to the unique patterns of regional cortical change during development. Metamemory monitoring at the first time point predicted intelligence at the third time point and vice versa, suggesting parallel development of these abilities and their reciprocal influence. Together, these results provide insights into the neuroanatomical correlates supporting the development of the capacity to self-reflect, and highlight the role of this capacity for general intellectual development.
DOI: 10.15154/1421920
title: Placental gross shape differences in a high autism risk cohort and the general population.

description: A growing body of evidence suggests that prenatal environment is important in Autism Spectrum Disorder (ASD) etiology. In this study, we compare placental shape features in younger siblings of children with ASD, who themselves are at high ASD risk, to a sample of low risk peers.  Digital photographs of the fetal placenta surface and of the sliced placental disk from 129 high ASD risk newborns and from 267 newborns in the National Children’s Study Vanguard pilot were analysed to extract comparable measures of placental chorionic surface shape, umbilical cord displacement and disk thickness. Placental thickness measures were moderately higher in siblings of ASD cases. The placentas of ASD-case siblings were also rounder and more regular in perimeter than general population placentas. After stratification by sex, these across-group differences persisted for both sexes but were more pronounced in females.  No significant differences were observed in cord insertion measures.  Variations in placental shape features are generally considered to reflect flexibility in placental growth in response to changes in intrauterine environment as the placenta establishes and matures.  Reduced placental shape variability observed in high ASD risk siblings compared to low-risk controls may indicate restricted ability to compensate for intrauterine changes.
DOI: 10.15154/1421921
title: Unravelling the Collective Diagnostic Power Behind the Features in the Autism Diagnostic Observation Schedule

description: Background: Autism is a group of heterogeneous disorders defined by deficits in social interaction and communication. Typically, diagnosis depends on the results of a behavioural examination called the Autism Diagnostic Observation Schedule (ADOS). Unfortunately, administration of the ADOS exam is time-consuming and requires a significant amount of expert intervention, leading to delays in diagnosis and access to early intervention programs. The diagnostic power of each feature in the ADOS exam is currently unknown. Our hypothesis is that certain features could be removed from the exam without a significant reduction in diagnostic accuracy, sensitivity or specificity. 

Objective: Determine the smallest subset of predictive features in ADOS module-1 (an exam variant for patients with minimal verbal skills).

Methodology: ADOS module-1 datasets were acquired from the Autism Genetic Resource Exchange and the National Database for Autism Research. The datasets contained 2572 samples with the following labels: autism (1763), autism spectrum (513), and non-autism (296). The datasets were used as input to 4 different cost-sensitive classifiers in Weka (functional trees, LADTree, logistic model trees, and PART). For each classifier, a 10-fold cross validation was preformed and the number of predictive features, accuracy, sensitivity, and specificity was recorded.

Results & Conclusion: Each classifier resulted in a reduction of the number of ADOS features required for autism diagnosis. The LADtree classifier was able to obtain the largest reduction, utilizing only 10 of 29 ADOS module-1 features (96.8% accuracy, 96.9% sensitivity, and 95.9% specificity). Overall, these results are a step towards a more efficient behavioural exam for autism diagnosis.
DOI: 10.15154/1422371
title: Measuring the individual benefit of a medical or behavioral treatment using generalized linear mixed-effects models

description: A statistical measure of the individual benefit of medical or behavioral treatment and of the severity of a chronic illness is proposed, which are used to develop a graphical method that can be used by statisticians and clinicians in the data analysis of clinical trials from the perspective of personalized medicine. 
The method focuses on assessing and comparing individual effects of treatments rather than average effects and can be used with continuous and discrete responses under generalized linear mixed-effects models framework. Analyses of data from the Sequenced Treatment Alternatives to Relieve Depression clinical trial of sequences of treatments for depression and data from a clinical trial of respiratory treatments are used for illustration.
DOI: 10.15154/1422780
title: Bayesian Meta-Analysis of Multiple Continuous Treatments: An Application to Antipsychotic Drugs

description: Modeling dose-response relationships of drugs is essential to understanding their eect on patient
outcomes under realistic circumstances. While intention-to-treat analyses of clinical trials provide
the eect of assignment to a particular drug and dose, they do not capture observed exposure
after factoring in non-adherence and dropout. We develop Bayesian methods to 
exibly model
dose-response relationships of binary outcomes with continuous treatment, allowing for treatment
eect heterogeneity and a non-linear response surface. We use a hierarchical framework for meta-
analysis with the explicit goal of combining information from multiple trials while accounting
for heterogeneity. In an application, we examine the risk of excessive weight gain for patients
with schizophrenia treated with the second generation antipsychotics paliperidone, risperidone,
or olanzapine in 14 clinical trials. Averaging over the sample population, we found that olanzapine
contributed to a 15.6% (95% CrI: 6.7, 27.1) excess risk of weight gain at a 500mg cumulative dose.
Paliperidone conferred a 3.2% (95% CrI: 1.5, 5.2) and risperidone a 14.9% (95% CrI: 0.0, 38.7)
excess risk at 500mg olanzapine equivalent cumulative doses. Blacks had an additional 6.8% (95%
CrI: 1.0, 12.4) risk of weight gain over non-blacks at 1000mg olanzapine equivalent cumulative
doses of paliperidone.
DOI: 10.15154/1423206
title: Data-Driven Generation of Synthetic Behavioral Feature Vectors Modeling Children with Autism Spectrum Disorders

description: Behavioral data on children with Autism Spectrum Disorders (ASD) are available thanks to standardized diagnostic tools, such as the Autism Diagnostic Observation Schedule (ADOS). This data can be of great use to enhance the learning and reasoning of agents interacting with children with ASD. However, the amount of such available data is limited and may not prove useful by itself to inform the algorithms of complex agents. To address this data scarcity problem, we present a method for generating synthetic behavioral data in the form of feature vectors characterizing a wide range of children with ASD. Our method relies on a thorough analysis and partition of the feature space based on a real dataset containing the ADOS scores of 279 children. We first analyze the real dataset using dimensionality reduction techniques, then introduce data-driven descriptors that partition the feature space into regions naturally arising from the data. We end by presenting a descriptor-based sampling method to generate synthetic feature vectors that successfully preserves the correlation structure of the real dataset.