Authors : Pasmas Coffie; Moses Mayonu; Onuh Matthew Ijiga

Volume/Issue : Volume 11 - 2026, Issue 5 - May

Google Scholar : https://tinyurl.com/2t9ef8bp

Scribd : https://tinyurl.com/yc73kawh

DOI : https://doi.org/10.38124/ijisrt/26May650

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Early detection of genetic predisposition to stroke remains constrained in low-resource clinical environments due to the high cost and technical demands of sequencing-based platforms. This study presents a novel Cost-Optimized PCRElectrophoresis Genotyping Framework (COPE-GF) designed for rapid, accurate, and affordable identification of strokeassociated genetic variants. The framework integrates targeted polymerase chain reaction amplification with optimized agarose gel electrophoresis and simplified band-pattern interpretation for key polymorphisms linked to ischemic stroke risk. The method was validated using clinical samples collected from laboratory settings in Ghana, focusing on variants within genes implicated in vascular integrity and inflammatory response. COPE-GF was systematically compared with five established genotyping approaches including Sanger sequencing, next-generation sequencing, TaqMan SNP genotyping assays, microarray-based genotyping, and high-resolution melt analysis. Evaluation metrics included accuracy, turnaround time, cost-efficiency, and technical accessibility. Results indicate that COPE-GF achieves competitive sensitivity and specificity while significantly reducing operational costs and infrastructure requirements. Although sequencing methods provide higher resolution, the proposed framework demonstrated strong concordance for targeted variant detection and offers substantial advantages in scalability for routine screening. This study establishes COPE-GF as a practical alternative for genomic screening in stroke risk assessment, particularly in resource-constrained healthcare systems, and supports broader implementation of molecular diagnostics in decentralized clinical settings.

Keywords : Stroke Genotyping; PCR-Based Molecular Diagnostics; Gel Electrophoresis Optimization; Low-Cost Clinical Genomics; Resource-Limited Laboratory Systems.

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