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Race and Genetics in Congenital Heart Disease: Application of iPSCs, Omics, and Machine Learning Technologies
McKay Mullen1,2, Angela Zhang1,3, George K Lui1,4,5
1Stanford Cardiovascular Institute, Stanford University, Stanford, CA, United States.
Insights
Congenital heart disease (CHD) disproportionately affects racial minorities. Induced pluripotent stem cells (iPSCs) offer a novel approach to investigate genetic disparities and improve treatment for diverse patient populations.
Area of Science:
- Cardiovascular Research
- Genetics
- Regenerative Medicine
Background:
- Congenital heart disease (CHD) involves structural heart abnormalities present at birth.
- Etiology and treatment disparities persist, particularly affecting racial minorities with worse prognoses.
- Environmental and genetic factors likely contribute to observed differences in CHD incidence and outcomes.
Purpose of the Study:
- To review the prevalence, risk factors, and genetics of CHD.
- To explore the role of induced pluripotent stem cells (iPSCs) in investigating race-specific genetic variants in CHD.
- To examine the connection between CHD etiology, racial disparities, and novel research technologies.
Main Methods:
- Review of existing literature on CHD prevalence, risk factors, and genetics.
- Discussion of cardiovascular disease modeling using iPSCs.
- Integration of omics and machine learning technologies for etiological investigation.
- Exploration of iPSC-based disease modeling with genome editing and drug screening.
Main Results:
- iPSC technology provides a novel platform for studying potential race-specific genetic variants in CHD.
- Combined use of iPSCs, omics, and machine learning can elucidate CHD etiology and racial disparities.
- Translational potential exists for iPSC-based modeling in conjunction with genome editing and drug screening.
Conclusions:
- Understanding genetic and environmental disparities is crucial for addressing CHD in minority populations.
- iPSC-based cardiovascular disease modeling is a promising tool for personalized medicine approaches to CHD.
- Further research integrating advanced technologies can improve CHD outcomes and reduce health inequities.
Abstract:
Congenital heart disease (CHD) is a multifaceted cardiovascular anomaly that occurs when there are structural abnormalities in the heart before birth. Although various risk factors are known to influence the development of this disease, a full comprehension of the etiology and treatment for different patient populations remains elusive. For instance, racial minorities are disproportionally affected by this disease and typically have worse prognosis, possibly due to environmental and genetic disparities. Although research into CHD has highlighted a wide range of causal factors, the reasons for these differences seen in different patient populations are not fully known. Cardiovascular disease modeling using induced pluripotent stem cells (iPSCs) is a novel approach for investigating possible genetic variants in CHD that may be race specific, making it a valuable tool to help solve the mystery of higher incidence and mortality rates among minorities. Herein, we first review the prevalence, risk factors, and genetics of CHD and then discuss the use of iPSCs, omics, and machine learning technologies to investigate the etiology of CHD and its connection to racial disparities. We also explore the translational potential of iPSC-based disease modeling combined with genome editing and high throughput drug screening platforms.
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