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Transcriptomic Analysis of Alzheimer's Disease Pathways in a Pakistani Population
Tanmoy Mondal1, Zarish Noreen2, Christopher A Loffredo3
1Department of Biology, Howard University, Washington, DC, USA.
This study identified 16 differentially expressed Alzheimer's disease (AD) genes in a Pakistani population, highlighting the role of amyloid processing and neuroinflammation. Findings offer insights for developing early AD biomarkers.
Area of Science:
- Neuroscience
- Genetics
- Molecular Biology
Background:
- Alzheimer's disease (AD) is a growing neurodegenerative disorder, particularly affecting elderly populations globally and increasingly in developing nations like Pakistan.
- Understanding the genetic underpinnings of AD is crucial for developing effective diagnostic and therapeutic strategies.
Purpose of the Study:
- To characterize key genes, their expression levels, and molecular networks involved in Alzheimer's disease pathogenesis within a Pakistani population.
- To identify potential genetic biomarkers for early AD detection through a pilot case-control study.
Main Methods:
- Employed high-throughput qRT-PCR (TaqMan Low-Density Array) and Affymetrix Arrays for global gene expression profiling in 33 AD patients and controls.
- Utilized Ingenuity Pathway Analysis (IPA) to identify molecular networks and signature genes associated with AD pathogenesis, focusing on amyloid processing and related pathways.
Main Results:
- Confirmed 16 differentially expressed AD-related genes, with significant fold changes in CAPNS2 and CAPN1.
- Observed 61% and 39% of genes were significantly up- and downregulated, respectively, in AD patients compared to controls (p-value < 0.05).
- Identified key pathways including Amyloid Processing, Neuroinflammation Signaling, and ErbB4 Signaling, with top networks related to Neurological Disease and Organismal Injury.
Conclusions:
- The study presents a non-invasive method combining TLDA and global gene expression analysis using whole blood for investigating AD.
- Findings provide valuable insights into gene expression patterns, particularly in Amyloid Processing, suggesting potential for identifying sensitive, early AD biomarkers.
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