Lauren Weiss, PhD - US grants

DESCRIPTION (provided by applicant): This application addresses Recovery Act Limited Competition: Research to Address the Heterogeneity in Autism Spectrum Disorders (R21) with RFA-MH-09-172. Autism spectrum disorders are among the most heritable common disorders and show extensive clinical heterogeneity, however, both the underlying neurobiological basis and genetic architecture are poorly understood. Four times as many males as females are affected, for unknown reasons. Thus, we may be able to leverage our knowledge about the primary genetic and hormonal determinants of sexual dimorphism in order to dissect a major source of heterogeneity in autism. The long-term goal is to use genetic tools to better understand the biological basis of autism, leading to advances in diagnosis, prevention and treatment. The objective of this proposal is to investigate genetic causes for increased male risk of autism. The central hypothesis is that sexually dimorphic susceptibility to autism is reflected in sex differences of the genetic architecture of autism. Guided by preliminary data including sex-specific genetic contributors to autism and extensive sexually dimorphic genetic architecture for numerous human traits, this proposal comprises a pilot to recruit subjects and compare males and females in order to distinguish genetic models and to identify sex-specific susceptibility loci. The specific aims include: 1) Recruitment of an enriched female-affected family sample, 2) Investigation of the genetic architecture of autism in females vs. males, and 3) Identification of the sex-specific genetic mechanisms or pathways involved in autism. The first aim will be accomplished by enrolling subjects retrospectively and prospectively from the UCSF Autism Clinic, enrolling subjects from an online autism community, and performing genome-wide SNP and CNV genotyping using the Affymetrix 6.0 microarray. The second aim will be accomplished by comparing family history, ascertainment, and measures of autism traits as well as comparing copy number profiles and summary SNP association signal between males and females. The third aim will be accomplished by analysis of sex-specific association signals, epistasis including X chromosome loci, and hormone-regulated gene pathway association. This approach is innovative, as sex-specific genetic architecture has not been comprehensively analyzed in a well-powered dataset, and we thus expect to gain novel insight into an important source of heterogeneity in autism. The results will be significant, as information about what protects females from developing autism could lead to reduction of male risk. PUBLIC HEALTH RELEVANCE: Autism is a common cause of severe disability to individuals and families across the lifespan with extremely limited treatment options. With better understanding of the biological basis and the genetic architecture of autism, diagnosis, prognosis, prevention and treatment options could be improved.

DESCRIPTION (Provided by the applicant) Abstract: The era of the genome promised that human genetics would quickly translate into personalized medicine. Genome-wide association studies on large samples from human populations have indicated that main effects of common polymorphisms or rare variants are unlikely to lead to improved ability to predict disease risk and therapeutic response. Epistasis (gene-gene interaction) and pleiotropy (diverse effects of the same gene) are known to play major roles in the genetic architecture of complex traits in model organisms, but have not yet been explored in human biology. This project aims to overcome the current challenge in human genetics in an innovative way by studying autism traits in congenital disorders of the Ras-MAPK pathway. Autism is a complex heritable disorder affecting nearly 1% of the population, and like most complex genetic disorders, the heritability is unaccounted for by current models of genetic association. Ras-MAPK diseases are genetic disorders with known mutations that include effects on craniofacial, cardiac, cutaneous, musculoskeletal and ocular development, as well as carrying increased risk of cancer and varying expression of neurocognitive impairment. Our preliminary data shows that these disorders are strongly associated with autism and that common polymorphisms in the same genes are associated with idiopathic familial autism. Therefore, Ras-MAPK pathway disorders provide an ideal model by which to explore epistasis and pleiotropy in the complex trait of autism. We will ascertain subjects with Ras-MAPK disorders, measure autism-related traits, and perform genome-wide mapping for interactors with the known Ras-MAPK genes. We will then establish induced pluripotent stem cell models from fibroblasts of patients with these disorders in order to investigate expression and functional assays utilizing cells differentiated into varying fates. This project has great translational potential not only for understanding how genetic variants mediate disease risk, but also with immediate implications for treatment approaches. Public Health Relevance: Autism Spectrum Disorders have recently been estimated to affect nearly 1% of Americans, and can cause severe disability to individuals and families across the lifespan with extremely limited treatment options. With better understanding of the genetic architecture of autism and causes of common co-morbidities, diagnosis, prognosis, prevention and treatment options could be improved. This project could lead the way to translating genetics into medicine for other common complex genetic disorders.

? DESCRIPTION (provided by applicant): Our long-term goal is to use genetic tools to improve understanding, prevention, and treatment of neurodevelopmental disorders. The objective of this proposal is to use genetic-expression networks to identify genes responsible for CNV-associated behavioral phenotypes. The central hypothesis is that expression dysregulation of one or multiple genes in a CNV region may contribute to phenotypic expression and this can be explored by expression quantitative trait locus (eQTL) and association analysis. In support of this hypothesis, preliminary data show that 16p11.2-related phenotypes show brain-specific association with eQTL networks of 16p11.2 genes. This proposal comprises a novel transcriptomics approach to identify gene expression dysregulation effects underlying neurobehavioral phenotypes by: 1) generating eQTL networks for each gene within or bordering a CNV of interest, 2) testing each eQTL network for association with relevant phenotypes in idiopathic disease datasets and EMR-linked biorepositories, and 3) utilizing eQTL network and association results to address biological questions. We expect to gain insight into how CNVs containing many brain genes influence neurodevelopment. Our unique approach enabled by preliminary data and powerful biorepositories may identify biological pathways through which CNVs cause neuropathogenicity and by extension may lead to novel hypothesized modifiers of relevant endophenotypes that could be explored in the future.

Our long-term goal is to use genetic tools to improve understanding, prevention, and treatment of autism spectrum disorder (ASD). The objective of this proposal is to utilize knowledge about sexual dimorphism in complex traits to extend our understanding of the genetic basis of a major risk factor for ASD, male sex. The current hypothesis is that genetic sources of sexual dimorphism can occur at three levels: genomewide burden or liability threshold, specific genetic loci representing gene-sex interaction, and relevant pathways or sets of loci reflecting environmental sex contribution. In support of this hypothesis, previous work has shown that genomewide genetic burden can differ by sex in cases ascertained for disease status and even in controls, risk loci can be sex-specific, and polymorphisms differing in contribution to secondary sex characteristics by sex impact disease risk. Our preliminary data also shows that genetic architecture differs between common polymorphism and rare variant risk. In order to understand the action of sex-heterogeneous SNPs, we will expand and refine their definition, establish their pathways of action, and test their mechanism of sex- specificity. In order to establish a population baseline for sexual dimorphism of SNVs, we will assess both genome-wide mutational burden and specific loci for sex differences and apply any new knowledge to ASD data. Finally, we will utilize our knowledge about gene-sex interaction to identify functional noncoding genetic variation relevant for disease risk. We expect to establish expectations about sex differences in genetic architecture and show its utility to understanding disease biology. We will gain novel insight into complex genetic mechanisms contributing to idiopathic ASD with implications for treatment and pioneer a generally applicable approach for utilizing sex as a precision tool for complex genetic disease.