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Random Forest-Integrated Analysis In Ad And Late Brain Transcriptome-Wide Data To Identify Disease-Specific Gene Expression, Xinxing Wu, Chong Peng, Peter T. Nelson, Qiang Cheng

Sanders-Brown Center on Aging Faculty Publications

Alzheimer's disease (AD) is a complex neurodegenerative disorder that affects thinking, memory, and behavior. Limbic-predominant age-related TDP-43 encephalopathy (LATE) is a recently identified common neurodegenerative disease that mimics the clinical symptoms of AD. The development of drugs to prevent or treat these neurodegenerative diseases has been slow, partly because the genes associated with these diseases are incompletely understood. A notable hindrance from data analysis perspective is that, usually, the clinical samples for patients and controls are highly imbalanced, thus rendering it challenging to apply most existing machine learning algorithms to directly analyze such datasets. Meeting this data analysis challenge is …

Analysis Of High-Risk Pedigrees Identifies 12 Candidate Variants For Alzheimer's Disease, Craig C. Teerlink, Justin B. Miller, Elizabeth L. Vance, Lyndsay A. Staley, Jeffrey Stevens, Justina P. Tavana, Matthew E. Cloward, Madeline L. Page, Louisa Dayton, Alzheimer's Disease Genetics Consortium, Lisa A. Cannon-Albright, John S. K. Kauwe

Institute for Biomedical Informatics Faculty Publications

INTRODUCTION: Analysis of sequence data in high-risk pedigrees is a powerful approach to detect rare predisposition variants.

METHODS: Rare, shared candidate predisposition variants were identified from exome sequencing 19 Alzheimer's disease (AD)-affected cousin pairs selected from high-risk pedigrees. Variants were further prioritized by risk association in various external datasets. Candidate variants emerging from these analyses were tested for co-segregation to additional affected relatives of the original sequenced pedigree members.

RESULTS: AD-affected high-risk cousin pairs contained 564 shared rare variants. Eleven variants spanning 10 genes were prioritized in external datasets: rs201665195 (ABCA7), and rs28933981 (TTR) were previously …

Meta-Analysis Of Natural Vs Pharmaceutical Interventions For Alzheimer's Disease, Tamara Vrublevskaya

Master's Projects

The purpose of this research is to present a way to compare interventions by collecting all available drug clinical trials for a disease of interest. The assessment is done using Meta-Analysis, a method for evaluating data from several studies to arrive at a combined estimate of treatment effect. The evaluation is done in R on a given set of studies to answer the question – which Alzheimer's Disease intervention (pharmaceutical vs. natural) show better outcomes and fewer adverse effects. The research covers many types of interventions across diverse patient populations. On a small subset of papers, natural treatments showed better …