2025 Summer Research Symposium • Rolando Ramos • July 9, 2025

Rolando Ramos

Class of 2026

Major: Biology

Mentor: Richard Cardenas, PhD, St. Mary’s University

Leveraging MATLAB for Genomic Analysis of Alzheimer’s Disease Risk

Genes in GWAS Datasets

Alzheimer’s disease (AD) is a complex neurodegenerative disorder influenced by both

environmental and genetic factors. My research emphasizes a bioinformatics pipeline using

MATLAB, a data analysis tool, to analyze genome-wide association study (GWAS) data

intended to pinpoint key genetic variants involved in AD. This method allows for large-scale

genomic interrogation while minimizing manual processing errors. We are particularly interested

in loci linked to well-established risk genes such as APOE, BIN1, and TREM2. Publicly

available datasets, including the Gene Expression Omnibus (GEO) and Alzheimer’s Disease

Neuroimaging Initiative (ADNI), are being processed to extract and purify relevant genotypic

and expression data. Mat lab serves as a versatile engine to organize, clean, and statistically

evaluate the data, integrating functions from the Bioinformatics Toolbox to conduct SNP

filtering, allele frequency analysis, and genomic variant visualization. Efficient comparison

between control and AD samples are displayed through effective methodology. Differential

expression and variant patterns support findings reported in current literature. Insights from this

analysis may reveal patterns that inform both diagnostic strategies and therapeutic research.

Early identification of high-risk alleles allow for more personalized and proactive clinical

interventions. This approach not only streamlines data analysis but also provides a standardized

and scalable framework for future investigations. We aim to capture a deeper understanding of

the molecular basis of AD and support efforts in preventive health by identifying early genetic

risk factors. This research underscores the potential of computational biology in advancing

precision medicine and demonstrates how technical tools like MATLAB can be applied in

genomic medicine.

Keywords: Alzheimer’s disease, genome sequencing, GWAS, SNP analysis, APOE,

BIN1