Dr. Go is a genetic epidemiologist with experience in the genetic analyses of complex diseases and traits, which includes population and family based genetic association tests, genetic linkage, genetic admixture, and linkage disequilibrium analyses. His research activities include: identifying new genes to confer susceptibility to Familial Alzheimer's Disease and schizophrenia; studying the genes which confer susceptibility to infectious and autoimmune diseases; investigating the interplay between the immune system and age; and studying the interplay of genetics and environmental factors in cardiovascular disease, dementia, hypertension, renal disease, diabetes, hemochromatosis, and mental disorders. Currently he is using a whole epigenome approach to identify epigenetic signals that confer increased risk to Parkinson’s disease due to exposures to plantation work and organochlorines in a unique population of Japanese males enrolled in the Honolulu Heart Program and Honolulu Asian Aging Study.
Epigenetics of Parkinson’s Kuakini Honolulu Heart Program Japanese Male Disease in the Population (Go, PI)
This project funded by the Michael J Fox Foundation for Parkinson’s Disease has as its goal to identify epigenetic differentially methylated loci that identifies cases of Parkinson’s Disease (PD) that have been exposed to plantation work and organochlorines, both identified in longitudinal studies of this population to be risk factors for PD. In addition it will seek to identify biomarkers for PD that are passed on as epigenetic marks to the children of this Japanese Male population.
Search for AD genes in the NIMH sibling dataset (Perry, PI)
This NINDS project is a continuation of the 1999 grant where we began analysis of a genome wide screen to identify late onset Alzheimer's disease genes and to identify candidate genes associated with AD in the regions of identity by descent sharing. This proposal will finish confirmatory follow-up analyses of the 11 CRI and continue genotyping polymorphisms in candidate genes for family-based association testing.
The following research projects on schizophrenia emulated from an original grant funded by NIMH, Project on African Americans to Explore Risks to Schizophrenia (PARTNERS) a consortium of 5 clinical sites, UAB being one and served as the Data Coordinating site with Dr. Go as PI.
Genome-Wide Methylation Scan for Epigenetic Contributions to Schizophrenia (Perry, PI)
The aims of this project funded by NIMH is to identify epigenetic signals through a genome wide methylation scan that confers risk to schizophrenia in subjects identified in a consortium of three patient populations. Three brain regions affected in schizophrenia patients will be also scanned to identify differential signals between a subset of cases and controls. The top 50 signals will be subjected to gene expression studies and fine mapping. This project will also integrate epigenetic and genetic variations to identify DNA variation that confers increased risk to schizophrenia and its related phenotypes.
Genetics of Transcriptional Endophenotypes for Schizophrenia (Perry,PI)
The aims of this study is to assay RNA transcriptional levels in lymp[hoblastoid cell lines for 5250 individual (including probands, family members, and controls) from three long standing NIMH funded cohorts (COGS, MGI, and PAARTNERS-UAB), and then identify genes whose expression is genetically correlated with schizophrenia (SZ) and associated neurocognitive endophenotypes. It will also conduct traditional GWAS analyses for SZ and neurocognitive genotypes using combined linkage and association methods and combine these results with genes from the expression analyses to localize genes influencing SZ and their associated endophenotypes. Finally it will use these results to perform functional analyses to confirm roles for selected genes in neuronal cell lines and brain tissues from SZ subjects.
Genomic Approach to Shizophrenia (GENESIS) (Savage-PI)
In this project we integrate genomic and transcriptomic approaches, by first identifying genes mutant in schizophrenia and then mapping their co-expression in the developing brain. To this end, we identified genes harboring de novo putatively damaging mutations in persons with De novo mutations in schizophrenia from otherwise healthy families. We then evaluated the extent to which the proteins encoded by these genes interact, and the extent to which they are transcriptionally coexpressed in different brain regions across developmental stages. The co-expression and protein interaction profiles were used to generate networks whose interconnectedness was quantifiable by the number of connections (edges) between implicated genes. Across brain regions and
developmental stages, we compared the interconnectedness of networks of genes harboring de novo mutations in probands versus networks from 10,000 simulations of genes harboring de novo mutations in controls.