Wang (Li-San) Lab
Principal Investigator: Li-San Wang, PhD
The Wang Lab focuses on Alzheimer’s disease and other neurodegenerative disorders, aging, and psychiatric disorders including autism and bipolar disorder.
Ongoing projects in the lab are as follows:
1) The Wang Lab participated in the analysis of several large-scale genome-wide association (GWA) studies, which led to findings of new risk genes for frontotemporal dementia (FTD) [Van Deerlin et al. 2010], progressive supranuclear palsy (PSP) [Höglinger et al. 2011], and late-onset Alzheimer’s disease (AD) [Naj et al. 2011]. Our lab is a participant of the Alzheimer’s Disease Genetics Consortium (ADGC), the largest collaborative project in United States to study AD genetics and the team behind the Nature Genetics article in 2011. In 2010, ADGC was one of the four founding consortia of International Genomics Alzheimer’s Project (IGAP) that substantially increased sample size and detected many additional candidate AD risk genes.
Our lab also contributes to the AD genetics research community in general. We have received a five-year grant (U24-AG041689) that will develop the NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) into a one-stop portal for access to all AD genetics studies sponsored by NIA. With the new NIAGADS, users will be able to access an AD genomics database, enhancement to house high-throughput sequencing data and analysis results, workflow and secondary data sharing for AD genetics research either using Amazon cloud or installing on their own local computing infrastructure, and an outreach program to promote data re-analysis and collaboration.
2) Our lab actively develops novel algorithms and computer programs that analyze GWA and DNA-seq studies. Currently we are working on a pipeline that analyzes whole-exome or whole-genome resequencing studies. The workflow is used in the analysis of 14 parent/proband trios in a multi-institutional study on autism that was recently published in Nature [Neale et al. 2012], and being used by several groups at Penn School of Medicine and Children’s Hospital of Philadelphia to study cancer, bipolar disorder, and other rare mendelian disorders. We are an active informatics participant of the Center for Personalized Diagnostics (CPD) initiative at the Department of Pathology and Laboratory Medicine. CPD will develop CLIA/CAP-compliant genetic tests using next generation sequencing for the Hospital of the University of Pennsylvania (HUP).
Our lab has been collaborating with Brian Gregory’s lab in the Department of Biology on RNA-seq methodology, i.e. the analysis of RNA processing and function using high throughput sequencing. Our paper in PLoS Genetics [Zheng et al. 2010] was one of three initial publications that used a novel RNA-seq protocol to study RNA secondary structure: Gregory lab developed the sequencing protocol and my lab developed the algorithm that folds transcripts into secondary structures using RNA-seq data. Subsequent studies using this technology led to a paper in the inaugural issue of Cell Reports [Li et al. 2012 Cell Reports] and the first web server (SAVoR) that generates annotated models of RNA secondary structures using RNA-seq experiments [Li et al. 2012 NAR].
3) Our lab is involved in developing biomarkers for aging and neurodegenerative disorders. As age is the biggest risk factor of Alzheimer’s disease, a reliable biomarker on physiological age will allow us to better examine the (causal) relations between age and neurodegeneration. We pioneered in using brain gene expression to estimate age of an individual, and showed that patients with AD and FTD exhibited accelerated aging in their brain [Cao et al. 2010]. The same method was used to show deficiency in the micro-RNA mir-34 leads to accelerated aging and brain degeneration in fruit flies, and provide possible mechanistic link between aging and neurodegeneration [Liu et al 2012].
We received a three-year grant to conduct a collaborative research between University of Pennsylvania and Johnson & Johnson Pharmaceutical Research and Development. The three-year project will analyze the Integrative Neurodegenerative Disease Database (INDD) from the Center for Nuerodegenerative Disease Research (CNDR) that tracks longitudinally ~11,000 patients that attended four clinics on neurodegenerative disorders at HUP. The database is invaluable as it contains a wealth of information such as cognitive tests, autopsy, MRI, and proteomic assays of hospital populations as opposed to controlled studies and clinical trials. This project will lead to better characterization of disease progression, robust identification of controls and AD patients for clinical studies, and more sensitive early diagnosis of Alzheimer’s disease.