Alzheimer's disease (AD) is a devastating complex neurological degenerative disorder affecting 10% of people over 65 with no cure. The overarching goal of the proposed study is to identify and functionally characterize AD-associated SNPs utilizing novel functional genomic approaches and iPSC-derived cellular models. Our plans include: (1) Determine the functional significance of candidate SNPs in three iPSC-drived 2D AD relevant cell types. (2) Identify genes regulated by distal non-coding SNPs in three iPSC-drived 2D AD relevant cell types. (3) Test the biological consequences of high confidence AD rSNPs from (1) and (2) in isogenic iPSC- derived 2D cell cultures and 3D minibrain organoids. The designed study will be very first comprehensive investigation of AD associated SNPs, thus will shed light on how non-coding genetic variations contribute to AD. Obtaining knowledge for the fundamental genetic mechanisms of AD will expand our horizons to develop improved preventative and diagnostic methods, and also yield targets for novel therapeutic interventions, ultimately leading to a cure for AD.

Public Health Relevance

Since most of these AD associated SNPs are located in the non-coding regions, further investigation of how genetic variations at these elements contribute to AD, has been thwarted. This proposal aims to understand how genetic variations at cis-regulatory sequences contribute to the risk of AD by integrating both functional genomics and iPSC-derived 2D and 3D cellular models. Obtaining knowledge for the fundamental genetic mechanisms of AD will expand our horizons to develop improved preventative and diagnostic methods, and also yield targets for novel therapeutic interventions, ultimately leading to a cure for AD.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG057497-03
Application #
9719716
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Wise, Bradley C
Project Start
2017-09-30
Project End
2022-05-31
Budget Start
2019-06-15
Budget End
2020-05-31
Support Year
3
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Neurology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118
Li, Yun; Hu, Ming; Shen, Yin (2018) Gene regulation in the 3D genome. Hum Mol Genet 27:R228-R233
Yoon, Ki-Jun; Vissers, Caroline; Ming, Guo-Li et al. (2018) Epigenetics and epitranscriptomics in temporal patterning of cortical neural progenitor competence. J Cell Biol 217:1901-1914
Qian, Xuyu; Jacob, Fadi; Song, Mingxi Max et al. (2018) Generation of human brain region-specific organoids using a miniaturized spinning bioreactor. Nat Protoc 13:565-580
Vissers, Caroline; Ming, Guo-Li; Song, Hongjun (2017) Stem cells take the stairs. J Biol Chem 292:19605-19606