BIOSTATISTICS AND BIOINFORMATICS CORE E ABSTRACT Project Summary Traditionally, much IDD research has focused on a single domain, e.g., either neuroimaging or behavior; either animal research or human research; either genetics or neuroimaging. Today, the state of the science is evolving into far more complex combinations of data from multiple viewpoints (e.g., genetic, neuroimaging, and behavioral data), which together can propel the next generation of IDD research aimed at discovering how to better identify, prevent, and intervene for those with IDDs. Thus, there is a great need to determine the most effective ways to combine and to analyze these multiple types and sources of data. Furthermore, for data types that are inherently multidimensional (e.g., genetics or neuroimaging), a second challenge becomes apparent: many of these approaches require big sample sizes. Therefore, an additional focus of Core E is to explore ways of effectively utilizing large repositories of data (BioVU/Synthetic Derivative). While these data sources are advantageous in size, navigating them is a daunting process for most investigators. Within this context, the overarching objective of Core E is to leverage the considerable statistical and bioinformatics expertise at VU and VUMC in order to push the current boundaries of design and analyses in the service of innovative discoveries in IDD. Against this backdrop, Core E has three aims:
Aim 1 is to provide statistical consultation to IDDRC investigators in implementing state-of-the art approaches to experimental design, statistical analysis, and interpretation of findings. Core E provides behavioral and biobehavioral statistical consultations to IDDRC investigators and their trainees who need guidance on basic or innovative research study design; efficient data collection and storage; proper method evaluation and implementation; and data analyses and interpretation.
Aim 2 is to develop new bioinformatics platforms for automation of data processing from multiple sources and to implement less widely used or novel data analysis approaches in IDD research.
Aim 3 is to create IDD- specific databases from large-scale electronic medical record and genomic resources at VUMC and to provide corresponding training and support services.
These Aims meet the needs of IDDRC investigators, including the U54 Research Project, while also generating new platforms, processes, and analytic methods that advance translational IDD science.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54HD083211-05
Application #
9547153
Study Section
Special Emphasis Panel (ZHD1)
Project Start
Project End
Budget Start
2018-06-01
Budget End
2019-05-31
Support Year
5
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Vanderbilt University Medical Center
Department
Type
DUNS #
079917897
City
Nashville
State
TN
Country
United States
Zip Code
37232
Simon, David M; Wallace, Mark T (2018) Integration and Temporal Processing of Asynchronous Audiovisual Speech. J Cogn Neurosci 30:319-337
Baranek, Grace T; Woynaroski, Tiffany G; Nowell, Sallie et al. (2018) Cascading effects of attention disengagement and sensory seeking on social symptoms in a community sample of infants at-risk for a future diagnosis of autism spectrum disorder. Dev Cogn Neurosci 29:30-40
Burke, Meghan M; Waitz-Kudla, Sydney N; Rabideau, Carol et al. (2018) Pulling back the curtain: Issues in conducting an intervention study with transition-aged youth with autism spectrum disorder and their families. Autism :1362361317753016
Ding, Zhaohua; Huang, Yali; Bailey, Stephen K et al. (2018) Detection of synchronous brain activity in white matter tracts at rest and under functional loading. Proc Natl Acad Sci U S A 115:595-600
Harbison, Amy L; Woynaroski, Tiffany G; Tapp, Jon et al. (2018) A new measure of child vocal reciprocity in children with autism spectrum disorder. Autism Res 11:903-915
Aboud, Katherine S; Barquero, Laura A; Cutting, Laurie E (2018) Prefrontal mediation of the reading network predicts intervention response in dyslexia. Cortex 101:96-106
Choi, Dahye; Conture, Edward G; Tumanova, Victoria et al. (2018) Young children's family history of stuttering and their articulation, language and attentional abilities: An exploratory study. J Commun Disord 71:22-36
Kim, Young-Suk Grace; Gatlin, Brandy; Al Otaiba, Stephanie et al. (2018) Theorization and an Empirical Investigation of the Component-Based and Developmental Text Writing Fluency Construct. J Learn Disabil 51:320-335
Bettis, Alexandra H; Forehand, Rex; Sterba, Sonya K et al. (2018) Anxiety and Depression in Children of Depressed Parents: Dynamics of Change in a Preventive Intervention. J Clin Child Adolesc Psychol 47:581-594
Mi, Deborah J; Dixit, Shilpy; Warner, Timothy A et al. (2018) Altered glutamate clearance in ascorbate deficient mice increases seizure susceptibility and contributes to cognitive impairment in APP/PSEN1 mice. Neurobiol Aging 71:241-254

Showing the most recent 10 out of 354 publications