Abstract Body: Background:
In recent years, induced pluripotent stem cell (iPSC) technologies have represented a promising technology for drug screening, disease modeling, and personalized medicine approaches. From these cell lines, researchers can differentiate iPSCs into cardiomyocytes (iPSC-CMs) and other somatic cell derivatives, which offers a platform to study cell characteristics in a patient-specific manner. The iPSC technology also addresses many challenges of previously used platforms, such as the inherent difference between rodent models and human physiology or the inaccessibility of human cell samples available via surgery or post-mortem. However, by characterizing cell lines from patients of different ancestries, researchers can better understand the race- and gender-specific phenotypes of heart disease. To demonstrate this, our study showed the successful generation of iPSC-CMs from two patients of African American ancestry and their applicability as patient-specific models.

Methods:
Our group isolated peripheral blood mononuclear cells (PBMCs) from two healthy African American patients, then reprogrammed the cells using Sendai virus vectors into two iPSC lines for generation: GSBi003-A and GSBi004-A. With these lines, reverse transcription-quantitative polymerase chain reactions (RT-qPCR) validated high expression levels of two pluripotency markers: NANOG and SOX2. Immunofluorescence staining confirmed the expression of pluripotency markers: NANOG, OCT3/4, and SOX2. Karyotyping showed normal karyotypes. Trilineage differentiation showed differentiation into all three germ layers: ectoderm, mesoderm, and endoderm. Short tandem repeat analysis verified the two lines’ concordance from their respective donors. Mycoplasma detection confirmed a mycoplasma-free contamination environment. From these methods, we demonstrated the successful characterization of two iPSC lines from two healthy African American patients.

Conclusion:
Our study validates the potential for patient-specific iPSC lines for drug screening and disease modeling to investigate cardiovascular diseases in a race- and gender-specific context. This platform has promising applications in developing therapeutics for heart disease.