THE GENETIC AND NEUROANATOMICAL ORIGIN OF SOCIAL BEHAVIOR PROJECT SUMMARY/ABSTRACT The overarching goal of this proposal is to gain insight into the plasticity of social behavior, and to identify the neuroanatomical and molecular determinants that contribute to social behavior. Social behavior is governed by both genetic and environmental factors, yet the genetic basis for normal social behavior remains poorly explored in spite of a need to better understand it for human health. This is underscored by numerous recent findings implicating dozens of susceptibility loci in autism spectrum disorders (ASDs), whose core features include marked deficits in social interaction. To gain insight into the underpinnings of social behavior, we propose to study abnormal social behavior in two mouse models of syndromic autism, the Tsc1 and Fmr1 mouse models. Single gene mutations account for a subset of syndromic ASD and mouse models of these disorders provide the opportunity to experimentally test and understand how these genes contribute to autism- like phenotypes. We hypothesize that social behavior is sensitive to the temporal requirement of either Tsc1 or Fmr1 gene function. We further hypothesize that specific neuronal populations are responsive to social stimuli, and that the loss of Tsc1 or Fmr1 may disrupt the pattern of neuronal activation in specific brain regions due to an underlying defect in common molecular targets.
The Specific Aims of the proposed work are i) investigate the temporal requirement of Tsc1 and Fmr1 for normal social behavior and the plasticity of social behavior by deleteing and restoring the expression of these genes'functions in the adult mouse brain using conditionally inducible mouse models, ii) identify the neuronal populations responsive to social stimuli and examine alterations in their activity in Tsc1 and Fmr1 mouse models by analyzing the pattern of immediate early gene expression during social interaction, iii) elucidate the molecular determinants of abnormal social behavior in Tsc1 and Fmr1 mouse models using RNA sequencing, two-dimensional liquid chromatography and mass spectrometry, and protein antibody microarray platforms. Because ASDs are a prominent public health concern with a current prevalence rate of 60 cases per 10,000 children, and in some populations more than 110 cases per 10,000 children, the proposed work is designed to determine if social behavior can be modified, and possibly corrected, in neuropsychiatric conditions during the adult stage of life.
The research aims will also inform us of the neuroanatomical determinants and molecular targets that may be critical in the manifestation of social behavior phenotypes. Together, our findings will provide the foundation for future work designed to improve social behavior phenotypes in humans by either genetic or pharmacological means.

Public Health Relevance

ASDs constitute a prevalent and devastating group of neuropsychiatric disorders affecting as many as 1:100 - 1:150 children. The proposed work will determine if social behavior deficits, such as those characteristic of ASDs, are reversible in adulthood, and will identify the neuroanatomical and molecular pathways that determine healthy social interactions. Defining the fundamental neuronal and molecular changes related to social behavior impairments has far-reaching benefits for human health, given that ASDs are a rising, prominent public health concern.

Agency
National Institute of Health (NIH)
Institute
Office of The Director, National Institutes of Health (OD)
Type
Early Independence Award (DP5)
Project #
3DP5OD009134-04S1
Application #
8915278
Study Section
Special Emphasis Panel (ZRG1-BBBP-E (53))
Program Officer
Basavappa, Ravi
Project Start
2011-09-20
Project End
2016-08-31
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
4
Fiscal Year
2014
Total Cost
$100,657
Indirect Cost
$37,084
Name
Baylor College of Medicine
Department
Genetics
Type
Schools of Medicine
DUNS #
051113330
City
Houston
State
TX
Country
United States
Zip Code
77030
Pang, Kaifang; Wan, Ying-Wooi; Choi, William T et al. (2014) Combinatorial therapy discovery using mixed integer linear programming. Bioinformatics 30:1456-63