I am a National Library of Medicine (NLM) Biomedical Informatics (BMI) fellow at both the Regenstrief Institute and the Center for Neuroimaging at Indiana University School of Medicine (IUSM). My career goal is to become a successful independent investigator with a focus on integrating bio-, medical, and imaging informatics approaches, including next generation sequencing (NGS) and advanced neuroimaging, to enhance the understanding of complex disease mechanisms and thereby facilitate development of novel treatments. The NLM BMI training program has been a priceless experience that enabled me to successfully transition my career from computational physics to biomedical informatics. During my three year NLM BMI fellowship, I gained extensive experience in advanced medical imaging analysis, medical informatics, bioinformatics, genomics, and statistics to prepare me to achieve my career goal. In order to consolidate my transdisciplinary skills and complete the transition to an independent researcher, my immediate career objective is to apply and expand my methodological skills and gain a broader understanding of current biological knowledge and future computational challenges in BMI. Using whole- exome sequencing pilot project data from the ongoing Alzheimer's Disease Neuroimaging Initiative (ADNI) as an initial learning platform, I will employ bio-, medical, and imaging informatics strategies in an integrated manner to identify functional rare variants associated with intermediate multi-modality phenotypes related to progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). Prior studies have identified a large number of common genetic variants but a substantial proportion of the heritability of AD remains unexplained by the known susceptibility genes. NGS can help close the gap by rare variant detection. The proposed research plan builds on my previous work in genome-wide association studies (GWAS) using imaging and medical informatics phenotypes and will expand my expertise to NGS. The rich ADNI data set provides a unique opportunity to address the challenges proposed in my specific aims and the IU Center for Neuroimaging serves as the ADNI Genetics Core which greatly facilitates data access and expert assistance.
Specific aims : (1) identify a subset of intermediate phenotypic biomarkers associated with a diagnosis of MCI/AD for genetic association analysis in the full ADNI sample set;(2) perform gene set- based association analysis of rare variants with MCI/AD-related intermediate phenotypic biomarkers in the ADNI whole-exome sequencing pilot project;and (3) validate novel variants and risk genes by imputing and genotyping target regions of detected genes in the full ADNI sample set.

Public Health Relevance

TO PUBLIC HEALTH: AD is an increasingly common neurodegenerative disease and the sixth leading cause of death in the United States. Identifying new susceptibility loci with functional impact on MCI progression will enhance mechanistic knowledge regarding AD pathways and may enable earlier diagnosis and treatment.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Career Transition Award (K99)
Project #
1K99LM011384-01
Application #
8352575
Study Section
Special Emphasis Panel (ZLM1-ZH-C (01))
Program Officer
Ye, Jane
Project Start
2012-09-01
Project End
2013-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
1
Fiscal Year
2012
Total Cost
$90,000
Indirect Cost
$6,667
Name
Indiana University-Purdue University at Indianapolis
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
603007902
City
Indianapolis
State
IN
Country
United States
Zip Code
46202
Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon et al. (2017) NETWORK-BASED GENOME WIDE STUDY OF HIPPOCAMPAL IMAGING PHENOTYPE IN ALZHEIMER'S DISEASE TO IDENTIFY FUNCTIONAL INTERACTION MODULES. Proc IEEE Int Conf Acoust Speech Signal Process 2017:6170-6174
Deters, Kacie D; Nho, Kwangsik; Risacher, Shannon L et al. (2017) Genome-wide association study of language performance in Alzheimer's disease. Brain Lang 172:22-29
Stage, Eddie; Duran, Tugce; Risacher, Shannon L et al. (2016) The effect of the top 20 Alzheimer disease risk genes on gray-matter density and FDG PET brain metabolism. Alzheimers Dement (Amst) 5:53-66
Nelson, Peter T; Katsumata, Yuriko; Nho, Kwangsik et al. (2016) Genomics and CSF analyses implicate thyroid hormone in hippocampal sclerosis of aging. Acta Neuropathol 132:841-858
Nho, Kwangsik; Ramanan, Vijay K; Horgusluoglu, Emrin et al. (2015) Comprehensive gene- and pathway-based analysis of depressive symptoms in older adults. J Alzheimers Dis 45:1197-206
Nho, Kwangsik; Saykin, Andrew J (2015) Reply: To PMID 25559091. Ann Neurol 78:499-500
Yan, Jingwen; Li, Taiyong; Wang, Hua et al. (2015) Cortical surface biomarkers for predicting cognitive outcomes using group l2,1 norm. Neurobiol Aging 36 Suppl 1:S185-93
Risacher, Shannon L; Kim, Sungeun; Nho, Kwangsik et al. (2015) APOE effect on Alzheimer's disease biomarkers in older adults with significant memory concern. Alzheimers Dement 11:1417-1429
Saykin, Andrew J; Shen, Li; Yao, Xiaohui et al. (2015) Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans. Alzheimers Dement 11:792-814
Yan, Jingwen; Kim, Sungeun; Nho, Kwangsik et al. (2015) Hippocampal transcriptome-guided genetic analysis of correlated episodic memory phenotypes in Alzheimer's disease. Front Genet 6:117

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