Recent advances in epidemiologic, brain-imaging, and genomic studies suggest that autism spectrum disorder (ASD) and schizophrenia (SCZ), two of the most heritable and pervasive neurodevelopmental disorders, may share some common etiologic mechanisms. While the two disorders are markedly distinct in terms of developmental trajectories and clinical presentations, it has long been recognized that there is considerable overlap of social cognitive deficits. It is thus a highly plausible yet unanswered question whether this overlap in social cognitive deficits reflects common etiological mechanisms, or represents superficial similarities due to comorbidity or misdiagnosis between these two illnesses. The applicant, Dr. Phil H. Lee proposes to address this research question through integrative neuroimaging genetic studies of ASD and SCZ, starting from genes to neural circuits, and ultimately to behavioral measures of social cognition. Owing to years? of efforts from worldwide collaborators, Dr. Lee now has access to large-scale genotype data (for genome-wide SNPs, N=32,921; for whole-exome-sequencing data, N=7,000) and an independent neuroimaging cohort of ASD, SCZ cases and healthy controls for whom a rich set of brain imaging and behavioral measures are available (N=3,752). Using these exceptionally powerful resources, she will investigate predictive relationships between common ASD and SCZ genetic risk burden and brain imaging/behavioral indexes of social cognitive functioning. The successful completion of this study will thus: (1) clarify how genetic variations at multiple levels (i.e., common and rare variants) influence brain structure/function and the development of core social deficits transcending traditional nosologic boundaries; (2) develop novel analytic strategies that are highly innovative and of general applicability to the studies of complex traits; and (3) lay the foundation for the development of biology-based prevention and remediation strategies for this core brain deficit. Dr. Lee?s career goal is to study the etiologic pathways of severe neurodevelopmental disorders, such as autism and schizophrenia, using an integrative analysis of genetic and neuroimaging data. This proposal builds on her postdoctoral training in psychiatric statistical genetics, centered on genome-wide association studies of a variety of neuropsychiatric disorders. While working towards accomplishing the proposed study, Dr. Lee will receive in-depth research training from world?s leading experts in computational genetics, clinical psychiatry, and cognitive neuroscience. This K99 Award will thus provide her with crucial and timely support to develop into an independent translational geneticist, who can effectively design and conduct neuroimaging genetic studies, ensure the validity, reliability and clinical applicability of the research work, and most importantly, is capable of translating the research findings into great public health benefits through the development of evidence-based prevention, diagnosis, and treatment strategies.
This project aims to elucidate the neural/genetic basis of social cognitive deficits commonly featured in autism spectrum disorder (ASD) and schizophrenia (SCZ). Our two-stage analysis consists of: (1) identification of susceptibility genes and biological pathways contributing risk to both ASD and SCZ; and (2) integrative statistical analysis of genetic and neural correlates of social cognition to infer their etiologic relationship. The successful completion of this project will lay the foundation for the development of effective prevention and remediation strategies for social cognitive deficits, which are key determinants of functional disability in ASD and SCZ due to a lack of effective treatment.
|Kim, Y; Giusti-Rodriguez, P; Crowley, J J et al. (2018) Comparative genomic evidence for the involvement of schizophrenia risk genes in antipsychotic effects. Mol Psychiatry 23:708-712|
|Chen, Chia-Yen; Lee, Phil H; Castro, Victor M et al. (2018) Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records. Transl Psychiatry 8:86|
|Ni, Guiyan; Moser, Gerhard; Schizophrenia Working Group of the Psychiatric Genomics Consortium et al. (2018) Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood. Am J Hum Genet 102:1185-1194|
|Brainstorm Consortium (see original citation for additional authors) (2018) Analysis of shared heritability in common disorders of the brain. Science 360:|
|Zhu, Zhaozhong; Lee, Phil H; Chaffin, Mark D et al. (2018) A genome-wide cross-trait analysis from UK Biobank highlights the shared genetic architecture of asthma and allergic diseases. Nat Genet 50:857-864|
|Lee, Phil H; Lee, Christian; Li, Xihao et al. (2018) Principles and methods of in-silico prioritization of non-coding regulatory variants. Hum Genet 137:15-30|
|Charney, A W; Ruderfer, D M; Stahl, E A et al. (2017) Evidence for genetic heterogeneity between clinical subtypes of bipolar disorder. Transl Psychiatry 7:e993|
|McLaughlin, Russell L; Schijven, Dick; van Rheenen, Wouter et al. (2017) Genetic correlation between amyotrophic lateral sclerosis and schizophrenia. Nat Commun 8:14774|
|Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium (2017) Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia. Mol Autism 8:21|
|Hibar, Derrek P (see original citation for additional authors) (2017) Novel genetic loci associated with hippocampal volume. Nat Commun 8:13624|
Showing the most recent 10 out of 14 publications