Cardiovascular disease (CVD) is the leading cause of death globally, affecting over 64 million people. But what’s even more alarming? It’s becoming a disease of the young. Today, 1 in 5 heart attack patients is under the age of 40 — a number that continues to rise.

While lifestyle factors like poor sleep, processed diets, and sedentary behavior are significant contributors, many young individuals are unknowingly carrying inherited risks. Genetic and epigenetic predispositions are silently passed through generations — and for most, they go undetected until it’s too late.

This creates a dangerous gap in prevention. Outwardly healthy young adults, including those with a family history of CVD, lack the tools to assess and act on their personal risk. The warning signs are genetic, but the warning systems are broken.

Here’s what’s not working:

• Wearables collect data, but it’s rarely translated into meaningful insights.
• Genetic testing exists, but most reports are confusing, lack clinical relevance, and offer no clear next steps.
• Epigenetic information is emerging, but it’s locked behind paywalls, jargon, or only accessible to researchers.

In short: CVD prevention is a maze. Fragmented, unclear, and too often reactive.

At CardioGenix, we believe it’s time to flip the system. By combining genomics, epigenetics, and AI, we aim to build a future where heart disease risk is no longer hidden — it’s revealed early, understood clearly, and managed personally.

We’re not just another health app. We’re the blueprint for personalized prevention.

Our Mission

At CardioGenix, our mission is to transform how we prevent and detect heart disease — before symptoms even begin. By combining advanced genetic and epigenetic data with AI-powered insights, we empower individuals with personalized tools, activities, and tracking systems to take control of their heart health. Unlike traditional healthcare, which reacts to symptoms, we focus on early detection and prevention. Our platform delivers actionable, accessible, and personalized guidance to help users build lasting lifestyle habits — anytime, anywhere.

Our Vision

We envision a world where healthcare is proactive, not reactive. Our long-term goal is to shift the paradigm from crisis-based treatment to personalized prevention — reducing avoidable deaths and helping people live longer, healthier lives. CardioGenix is especially focused on youth with a family history of heart disease, equipping them with the knowledge and tools they need to make informed, preventive choices today — before risk becomes reality.

Building a Smart Prevention Platform for Your Heart Health Profile

Most heart conditions develop silently — and traditional tests miss genetic markers and early risk signals. CardioGenix solves this by building a smart prevention platform powered by genomics, epigenetics, wearables, and AI.

Your DNA, lifestyle data, and real-time behaviors are synthesized to generate a dynamic heart health profile — with personalized guidance you can actually use.

Step 1: Get Genetically Informed
We start by analyzing your genetic data. You can either upload existing raw data from our partnered testing services powered by TruDiagnostic’s advanced epigenetic and genomic tools.

Step 2: Risk Assessment
Using AI-driven models and up-to-date research, we assess your genetic and epigenetic markers to identify your risk factors for cardiovascular diseases — before symptoms appear.

Step 3: Personalized Prevention Plan
Based on your unique profile, we generate a personalized heart health roadmap. This includes nutrition guidance, exercise plans, sleep recommendations, and stress-reducing habits — all tailored to your genetic makeup and lifestyle.

Step 4: Actionable Tracking
You’ll have access to a user-friendly dashboard that tracks your biomarkers, lifestyle habits, and health progress in real time. There will also be features to monitor your calorie intake. Our system integrates with wearables and health apps to ensure nothing is missed.

Step 5: Continuous Optimization
Your data isn’t static — neither is your plan. We continuously analyze changes and adapt your recommendations over time, helping you build sustainable habits and improve long-term heart health.

Step 6: Stay Ahead, Stay Empowered
We give you insights — not just data. CardioGenix turns complex genomics into everyday decisions, so you’re always one step ahead of cardiovascular risks.

CardioGenix Strategy

Year 1: Pilot + Validation

Objective: Build credibility, test product-market fit, and refine our platform experience.

• Using technology inspired by TruDiagnostics, we will offer advanced epigenetic testing for a select group of high-risk youth (e.g., South Asian, family history).
• Enroll 500 pilot users aged 18–35, providing:
• Full genetic and epigenetic risk analysis.
• Personal lifestyle risk reports.
• Preventive recommendations via our CardioGenix dashboard.
• Partner with clinicians, universities, and genetic counselors to validate outcomes.
• Launch our Alpha platform, combining wearables, lab data, and predictive analytics.

Measure:

• Change in risk awareness.
• User action on preventive behavior.
• Engagement with clinicians and reports.

Year 2: Expansion & AI Integration

Objective: Scale users, optimize UX, and enhance personalization.

Expand to 5,000 users through strategic partnerships with:

• University health centers.
• Corporate wellness programs.
• South Asian-focused health organizations
• Launch CardioGenix AI: A personalized insights engine integrating:
• Wearable data (e.g., HRV, sleep).
• Epigenetic age & methylation insights from TruDiagnostic.
• PRS (polygenic risk score) modules.
• Launch CardioGenix Connect: a portal for physicians and health coaches.
• Add baseline coaching service for high-risk users.

Years 3–4: Ecosystem Growth & Policy Alignment

Objective: Broaden impact and integrate with public health frameworks.

• Scale to 25,000+ users across North America.
• Publish findings from pilot + clinical studies on early intervention impact.
• Integrate API compatibility with Apple Health, Fitbit, WHOOP, etc.

Form alliances with:

• Provincial/state health departments.
• Health insurance providers (for preventive care credits).
• National genomic screening initiatives.
• Begin offering family risk tracking and longitudinal prevention plans.

Year 5 and Beyond: Global Scale + Platform Diversification

Objective: Become a global leader in cardiovascular genomics prevention.

• Expand to India, UK, and the Middle East, starting with high-risk communities.

Introduce:

• Multigenerational genomic risk reports.
• Microbiome + epigenome integration.
• Epigenetic age reversal coaching tracks.
• Use AI-generated insights to influence policy and public health prevention models globally.

Revenue Model

CardioGenix earns revenue through:

1. Direct-to-consumer subscriptions for genetic/epigenetic testing and ongoing analytics.
2. B2B partnerships with wellness programs, clinics, and universities.
3. Premium coaching and prevention plans for high-risk users.
4. API licensing to insurance providers for risk adjustment models.
5. Government partnerships and grants to bring genomic prevention to underserved populations.

Why CardioGenix Will Win

• First Mover in Precision Prevention: While many apps track lifestyle, none meaningfully combine static (genetic), dynamic (epigenetic), and behavioral (wearable) data.
• Lived Experience & Passion: Founded by those with personal stakes and cultural insight, CardioGenix is rooted in empathy, not just efficiency.
• Trustworthy Brand: We’re not selling data or just selling tests. We’re offering clarity, agency, and long-term health.

A Healthier Future, Powered by You

When you join CardioGenix, you’re not just using a product — you’re contributing to the future of precision-based, preventative cardiology. Our vision is a world where your zip code or ethnicity no longer determine your cardiovascular health outcomes.

This is how we stay ahead of heart disease — by making prevention personal, proactive, and accessible. And it all starts with you.

Abstract

Recent advancements in epigenetics and non-coding RNA research have underscored the critical role of microRNAs (miRNAs) in regulating vascular homeostasis. The discovery of miRNAs has revolutionized our understanding of endothelial dysfunction and its molecular underpinnings in diabetic pathogenesis. This proposal explores a dual-miRNA therapeutic approach targeting miR-21 and miR-126 to mitigate endothelial damage and promote vascular repair. miR-21 is a key driver of fibrosis and inflammation, frequently upregulated across various diseases, contributing to pathological cell proliferation. In contrast, miR-126 plays a crucial role in vascular protection by enhancing endothelial repair and mitigating vascular dysfunction in diabetic patients.

This proposal hypothesizes that a nanoparticle-based delivery system co-administering a miR-21 antagomir alongside a miR-126 mimic can synergistically restore endothelial function and reduce vascular complications associated with diabetes. This concept is reinforced by emerging preclinical evidence indicating that targeting these miRNAs has therapeutic potential in diabetic vascular disease. By leveraging RNA-based therapeutics and precision nanomedicine, this approach presents a novel, dual-action strategy to improve vascular health in diabetic patients, with potential implications for broader cardiovascular disorders.

Introduction

In recent years, significant advancements in epigenetics have revealed its profound implications for human cardiovascular disease (CVD). As highlighted in the paper Epigenetics and Cardiovascular Disease,

“Because epigenetic processes are dynamic and respond to environmental cues, they provide a conceptual framework for understanding the limitations of an approach to CVD research that focuses only on the importance of the static DNA code. Apart from deepening our understanding of disease mechanisms, epigenetics might contribute to groundbreaking future therapies and diagnostic tests.”

This underscores the immense potential of epigenetics in transforming cardiovascular health. In this article, a novel therapeutic approach to combating diabetic vascular disease will be explored — targeting miR-21 and miR-126, two key regulators of endothelial function, to enhance vascular repair and reduce disease progression.

Endothelial Dysfunction and Diabetic Vascular Disease

The prevalence of diabetes is rapidly increasing worldwide, making it one of the most significant health challenges of the 21st century. In 2019, over 460 million individuals were affected by the disease, and this number is projected to exceed 700 million by 2045. In the United States, diabetes ranks as the seventh leading cause of death, and in 2020 alone, it contributed to approximately 4.2 million deaths globally. The International Diabetes Federation emphasizes that diabetes is a critical public health issue that transcends socioeconomic and geographic boundaries.

Diabetes is a chronic metabolic disorder characterized by persistently high blood glucose levels, resulting from the body’s inability to produce sufficient insulin or effectively utilize it. Over time, this condition damages both small and large blood vessels, increasing the risk of severe complications. One of the most concerning long-term consequences is the heightened risk of cardiovascular disease (CVD). Research indicates that individuals with diabetes face a 70% greater likelihood of developing CVD and are two to six times more prone to experiencing a stroke compared to those without diabetes.

A key driver of diabetic vascular disease (DVD) is chronic hyperglycemia-induced endothelial dysfunction. Endothelial dysfunction affects the endothelium, which is a thin layer of cells inside of blood vessels. The dysfunction causes the blood vessels to constrict. This condition leads to excessive oxidative stress, chronic inflammation, and impaired angiogenesis, all of which contribute to the progression of atherosclerosis and other cardiovascular complications. While current treatments focus on controlling blood sugar levels and managing symptoms, there is a pressing need for innovative therapeutic strategies that target the underlying molecular mechanisms of the disease.

Both clinical and experimental studies have established that diabetes and insulin resistance significantly contribute to endothelial dysfunction, thereby weakening the vascular endothelium’s natural protective role against atherosclerosis. Furthermore, research suggests that endothelial dysfunction and insulin resistance often develop before noticeable hyperglycemia in individuals with type 2 diabetes, making them critical early intervention targets for preventing cardiovascular disease. In a healthy state, the endothelium maintains a balance between vasodilation and vasoconstriction. However, in individuals with diabetes and atherosclerosis, this balance is disrupted, leading to further vascular and organ damage (Tan et al., 2002).

Although multiple factors contribute to endothelial dysfunction in diabetes, hyperglycemia is considered the primary cause. Insulin resistance is also strongly associated with various health conditions that elevate cardiovascular risk and mortality, including obesity, hypertension, metabolic syndrome, and heart failure. Given the crucial role of endothelial dysfunction in diabetic vascular complications, further exploration of targeted therapies — particularly those focusing on molecular pathways such as miRNA regulation — may pave the way for more effective strategies to enhance vascular health in individuals with diabetes.

Overview of MicroRNAs

MicroRNAs have recently emerged as regulators of gene expression without modifying any such genetic sequences. They are small non-coding RNAs, approximately 18–25 nucleotides in length and have dramatically impacted modern-disease related molecular biological experiments. More than 2,500 miRNAs are currently identified in the human genome and over 60% of human genes are predicted to be regulated by these small RNAs (Zhang, 2008).

Due to the regulatory function miRNAs have as well as the ability to horizontally transfer from one cell type to another, they are mainly being used as “therapeutic drugs” to treat diseases by reversing or modulating the dysregulated miRNAs. The two main approaches used to restore the functions of disease-related cellular pathways are by using miRNA-mimics to restore downregulated miRNAs or inhibiting the upregulation and activity of specific miRNAs through chemically modified antisense oligonucleotides, known as antimiRs or antagomiRs. However, with regards to the promising potential of various mechanisms of specific miRNA, miRNA based therapeutics and biomarkers have yet to be approved to be implemented in a clinical setting.

MicroRNAs have been shown to contribute to several pathologic conditions, including cardiovascular disease. They have been found to be involved in the cardiac development, function, and progression of CVDs. Many miRNAs are master regulators fine-tuning the expression of multiple, often interrelated, genes involved in inflammation, apoptosis, fibrosis, senescence, and other processes crucial for the development of different forms of CVDs.

Role of miRNAs in Endothelial Dysfunction

miRNAs influence critical endothelial processes, including cell survival, proliferation, and inflammation. Dysregulation of specific miRNAs has been implicated in diabetic complications, making them attractive targets for therapeutic intervention.

MicroRNA-126 as a Therapeutic Agent

MicroRNA-126 is mainly expressed in endothelial cells and is defined as a pivotal biological molecule associated with vascular disease. Not only does it attenuate vascular dysfunction in diabetics, but it promotes angiogenesis in ischemic stroke and repairs impaired endothelial cells in atherosclerosis. (Qu, Yang, Ai et al., 2018)

One of the essential roles of miR-126 in endothelial cells is regulating angiogenesis and maintaining vascular integrity. It achieves this by targeting negative regulators of the vascular endothelial growth factor (VEGF) signaling pathway, such as SPRED1 and PIK3R2. By inhibiting these regulators, miR-126 enhances the activation of ERK and PI3K/Akt signaling pathways, which are critical for endothelial cell survival, migration, and the formation of new blood vessels.

Beyond its role in angiogenesis, miR-126 also possesses anti-inflammatory properties. It suppresses the expression of vascular cell adhesion molecule-1 (VCAM-1), which reduces leukocyte adhesion to endothelial cells. This process helps limit inflammation and prevents vascular damage that can result from excessive immune cell recruitment. By controlling immune cell interactions with the endothelium, miR-126 plays a crucial role in maintaining vascular health.

Additionally, miR-126 has an anti-apoptotic function, helping to protect endothelial cells from programmed cell death by targeting pro-apoptotic genes like TGFβ. This protective effect is particularly significant in environments with high glucose levels or oxidative stress, both of which are common in diabetes. Furthermore, miR-126 contributes to vascular stability by reducing arterial wall permeability and strengthening endothelial junctions. This function is especially important in preventing the progression of atherosclerosis and preserving vascular integrity under conditions such as hyperglycemia or high-fat diets (Cheng, Wan, Zhou et al., 2017).

MicroRNA-126 in Endothelial Dysfunction

In conditions like diabetes and atherosclerosis, miR-126 levels are significantly reduced in endothelial cells. This means that the loss of miR-126 leads to the absence of the functions this microRNA performs as. Moreover, high glucose levels reduce the release of miR-126 from endothelial apoptotic bodies leading to VEGF resistance and compromised vascular repair mechanisms (Zampetaki et al., 2010).

Supporting these findings, Yang et al. reported that experimental studies have shown endothelial microparticles derived from glucose-treated endothelial cells contain lower levels of miR-126, which in turn reduces endothelial repair capacity. This suggests that increasing miR-126 expression in glucose-damaged endothelial cells may help protect them from glucose-induced dysfunction, potentially restoring vascular repair mechanisms.

MicroRNA-21 as a Prospective Target

MicroRNA-21 is one of the first miRNAs to be discovered; it is encoded by the MIR21 gene and is located on the chromosomal positive strand 17q23.2. This biological molecule regulates many signaling pathways and therefore plays a crucial role in the cardiovascular system. With that said, it is involved in the differentiation and migration of endothelial cells and angiogenesis.

MicroRNA-21 in Endothelial Dysfunction

MiR-21 is a multifunctional miRNA that exerts both protective and pathological effects on endothelial cells, depending on the physiological context. On the protective side, miR-21 is known to regulate the biological functions of progenitor endothelial cells. Research by Bracha et al. has demonstrated that exosomes derived from these progenitor cells contribute to vascular endothelial cell repair by delivering miR-21–5p. This process directly suppresses the expression of thrombospondin 1 (THBS1), an angiogenesis inhibitor in endothelial cells. Additionally, miR-21 enhances endothelial cell survival by inhibiting pro-apoptotic genes such as PDCD4 and PTEN, which results in increased nitric oxide production, reduced oxidative stress, and greater endothelial resilience. Studies conducted by Zeng and colleagues further support miR-21’s protective role, showing that it helps shield endothelial cells from glucose-induced cytotoxicity, likely by downregulating DAXX, a key factor in vascular diseases associated with diabetes.

Paradoxically, despite these protective functions, miR-21 also has detrimental effects under certain conditions. Excessive expression of miR-21 has been linked to impaired angiogenesis due to its suppression of RhoB, a gene essential for endothelial cell migration and tubulogenesis. This inhibition results in reduced endothelial proliferation, migration, and tube formation, which are critical processes for vascular repair. Furthermore, under conditions of low or oscillatory shear stress, miR-21 has been found to suppress anti-inflammatory pathways such as PPARα while activating pro-inflammatory pathways like AP-1. This activation promotes immune cell adhesion to endothelial cells, fostering inflammation and the development of atherosclerotic plaques. The ongoing cycle of inflammation and AP-1 activation drives miR-21 overexpression, potentially accelerating the progression of atherosclerosis (Holland et al., 2023).

Given miR-21’s role in both endothelial dysfunction and vascular inflammation, some researchers, including Zhou et al., suggest that inhibiting miR-21 may be an effective therapeutic approach. MiR-21 is widely recognized for its pro-fibrotic and pro-inflammatory characteristics, as its upregulation in diabetic endothelial tissues contributes to inflammatory cytokine release and worsening endothelial dysfunction. Targeting miR-21 could, therefore, be a promising strategy for mitigating vascular complications associated with diabetes and other cardiovascular diseases.

RAAS Activation in Diabetes and Its Impact on miRNAs

The Renin-Angiotensin-Aldosterone System (RAAS) plays a crucial role in endothelial dysfunction, a major contributor to cardiovascular diseases such as hypertension, atherosclerosis, and diabetes-related vascular complications. Dysregulation of RAAS, particularly due to elevated activity of angiotensin II (Ang II) and aldosterone, leads to increased oxidative stress, heightened inflammation, decreased nitric oxide (NO) bioavailability, and vascular remodeling. Aldosterone further worsens endothelial dysfunction by promoting oxidative damage, inducing arterial stiffness, and impairing insulin signaling. These pathological changes establish self-reinforcing cycles that accelerate vascular deterioration.

To counteract these harmful effects, pharmacological interventions targeting RAAS components — such as angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), aldosterone antagonists, and direct renin inhibitors — have been shown to reduce oxidative stress, suppress inflammation, and enhance endothelial function. While these treatments help slow disease progression, a dual miRNA-based therapeutic approach could provide a more precise and efficient means of regulating RAAS activity, potentially offering greater benefits in preventing diabetes-related vascular complications.

Dual-miRNA Therapy for Endothelial Dysfunction

Restoring endothelial function in diabetic vascular disease requires a multifaceted strategy addressing both the drivers of dysfunction and the mechanisms of repair. This article proposes a dual-miRNA therapeutic approach designed to counteract the detrimental effects of hyperglycemia-induced miRNA dysregulation while enhancing endothelial regeneration. By simultaneously inhibiting miR-21 and supplementing miR-126, this strategy aims to mitigate fibrosis, inflammation, and impaired angiogenesis — all hallmarks of diabetic endothelial dysfunction. The proposed approach leverages:

1. miR-21 Antagomir: This synthetic, single-stranded oligonucleotide is specifically designed to inhibit miR-21, a key contributor to endothelial dysfunction. By binding to miR-21, the antagomir prevents it from interacting with its target mRNAs, reducing pro-fibrotic signaling, inflammation, and excessive extracellular matrix deposition. By blocking the miRNA, antagomirs effectively increase the expression of the mRNA that would normally be downregulated by the mRNA. Inhibition of miR-21 has been shown to lower levels of TGF-β and other fibrotic markers, ultimately alleviating endothelial damage.
2. miR-126 Mimic: MiR-Mimic is an innovative approach used for gene silencing as it generates a chemically synthesized double-stranded miRNA-like RNA fragments. As a synthetic miRNA analogue, the miR-126 mimic functions to replenish endogenous miR-126 levels, which are typically suppressed in diabetic endothelial dysfunction. miR-126 is crucial for maintaining endothelial integrity by enhancing nitric oxide production, reducing leukocyte adhesion, and promoting endothelial progenitor cell recruitment. By restoring miR-126 expression, this therapy aims to improve endothelial repair and angiogenesis, counteracting the vascular damage induced by diabetes.

This dual approach directly targets the imbalance caused by hyperglycemia-induced epigenetic modifications, ensuring that while one pathway (fibrosis and inflammation via miR-21) is suppressed, another (vascular repair via miR-126) is enhanced. Such a complementary strategy increases the likelihood of restoring endothelial homeostasis more effectively than single-miRNA interventions. The co-administration of these miRNA-based therapeutics is a promising solutions for mitigating endothelial dysfunction in diabetic vascular disease.

Delivery Strategy: Nanoparticle-Based miRNA Therapy

Now that the our target microRNAs have been identified, a method of how we will be delivering the miR-21 antagomir and the miR-126 will be discussed. Relying on just naked miRNA-based agents as a solution will result in poor targeting ability, short circulation time, and off-target effects. To overcome these barriers, miRNA loaded nanoparticles are proposed as it is able to shield the loaded agent from the external environment, thereby reducing inactivation or degradation, and enhancing circulation time and targeted accumulation.

One type of loaded nanoparticle are lipid nanoparticles (LNPs), this is what will be used in the proposed solution. Lipid nanoparticles (LNPs) are highly versatile drug delivery systems used for the delivery of DNA, RNA, or non-coding RNAs (ncRNAs), with applications already in clinical use, particularly in cancer therapy and RNA-based treatments. The rationale behind selecting LNPs lies in their biodegradable, biocompatible, and customizable nature, allowing for precise engineering to maximize endothelial targeting and therapeutic efficacy. The design of an LNP system involves optimizing its structural components to enhance stability, circulation time, cellular uptake, and controlled release. The key components of the LNP formulation for this dual-miRNA therapy include:

• Ionizable Lipids: These lipids interact with the negatively charged miRNAs (both the miR-21 antagomir and miR-126 mimic), forming stable RNA-lipid complexes. Their ability to become positively charged in acidic environments, such as endosomes, facilitates endosomal escape, ensuring efficient intracellular delivery of the therapeutic payload.
• Cholesterol: Incorporated into LNPs to enhance structural integrity and improve membrane fusion, thereby increasing cellular uptake and maximizing the therapeutic action of the delivered miRNAs.
• PEGylated Lipids (PEG-Lipids): These components prevent rapid clearance by the immune system, extending circulation time in the bloodstream and increasing the likelihood of effective endothelial targeting. Additionally, PEG-lipids reduce nanoparticle aggregation, enhancing overall particle stability.
• Targeting Ligands (e.g., Peptides and Antibodies): Conjugating targeting ligands to the LNP surface enables active targeting by binding to specific endothelial cell receptors, ensuring precise delivery to vascular tissues. When combined with passive targeting mechanisms, such as the enhanced permeability and retention (EPR) effect, these ligands improve cellular uptake while reducing off-target effects.

To assess whether this technique has worked, several biomarkers can be used to evaluate efficiency. Inflammatory markers could be used to measure inflammatory levels of cytokines and adhesion molecules in plasma or tissue samples. A successful therapy should reduce these markers. As an alternative, nitric oxide levels can serve as an indicator of improved endothelial function. Increased NO production suggests restored endothelial homeostasis

By leveraging LNP-based delivery, this approach ensures that both the miR-21 antagomir and miR-126 mimic reach endothelial cells efficiently, maximizing their therapeutic impact. The stability of LNPs protects miRNAs from degradation, while their ability to release their cargo in a controlled manner further enhances the efficacy of dual-miRNA therapy.

Preclinical Evidence

Preclinical studies have provided strong evidence on how a lipid nanoparticle-based delivery using miR-21 antagomir and miR-126 mimic would help tackle endothelial dysfunction among diabetic patients. These findings prove from how targeting miR-21 would be beneficial, to why a combination therapy would ensure that the microRNA would positively impact the individual to whom the therapy was administer to. Below are some key findings from preclinical studies:

1. miR-21 Targeting RhoB and Angiogenesis (Capogrossi et al., 2011)

miR-21 negatively regulates angiogenesis by targeting RhoB, a small GTPase essential for endothelial cell (EC) migration and proliferation. Overexpression of miR-21 reduces RhoB expression, disrupting actin stress fiber formation and impairing EC migration and the ability to form capillary-like structures. In vitro studies using human umbilical vein endothelial cells (HUVECs) showed that miR-21 overexpression decreased tube formation and proliferation, while inhibition of miR-21 restored these angiogenic functions. In vivo, a mouse model of choroidal neovascularization demonstrated that miR-21 overexpression significantly inhibited new blood vessel formation. These findings make miR-21 a potential therapeutic target for diseases requiring enhanced vascular repair or controlled angiogenesis.

2. Role of miR-126 in Regulating Endothelial Permeability and Apoptosis (Cheng et al., 2017)

A study using apoE−/− mice fed a high-fat diet demonstrated that miR-126 expression was significantly reduced, leading to increased endothelial permeability and apoptosis. Treatment with a miR-126 mimic restored endothelial function by downregulating TGFβ, a key regulator of apoptosis, and maintaining Bcl-2 expression, a pro-survival protein. Conversely, a miR-126 antagomir worsened endothelial dysfunction, confirming miR-126’s protective role. The study also validated TGFβ as a direct target of miR-126 through luciferase assays, highlighting its mechanism in reducing endothelial damage. Since endothelial dysfunction is a hallmark of both AS and diabetic vascular disease, these findings strongly support the use of miR-126 mimics as a potential therapy for diabetes-induced vascular complications.

3. Combination of miRNAs

In models of non-small cell lung cancer, the combined delivery of miR-34a and let-7b, both tumor-suppressor miRNAs, led to a 5- to 8-fold reduction in invasive potential compared to single-agent therapy. This finding highlights the synergistic effect of combination miRNA therapies in inhibiting tumor progression. Although this example originates from oncology, it emphasizes the broader therapeutic potential of dual-miRNA approaches across various diseases.

A similar strategy could be applied to treating endothelial dysfunction by co-delivering miR-21 antagomirs and miR-126 mimics. This approach could simultaneously target multiple pathological pathways, potentially providing a more effective and comprehensive treatment for vascular complications. However, further preclinical studies are essential to assess the safety and efficacy of such combination therapies in the context of diabetes-induced endothelial dysfunction before clinical translation.

Limitations

While targeting miR-21 and miR-126 to reduce inflammation and promote endothelial repair presents a promising strategy for addressing endothelial dysfunction, particularly in individuals with diabetic vascular disease (DVD), several challenges and limitations must be carefully considered before clinical application. These concerns primarily include off-target effects, optimal dosing strategies, and long-term safety.

Although miRNA mimics and antagomirs can effectively target mRNAs associated with disease progression, several critical hurdles remain in developing miRNA-based therapies. As highlighted by Samanta et al., most in vivo studies have primarily focused on site-specific phenotypic effects, often overlooking potential off-target interactions in other tissues. To ensure safety and efficacy, future research must adopt a more systematic approach that evaluates miRNA activity across multiple organ systems rather than concentrating solely on localized effects.

One key aspect of optimizing miRNA delivery involves the use of lipid nanoparticles (LNPs) or other nanocarrier systems. These carriers enhance cellular uptake, improve circulation stability, and enable precise endothelial targeting. However, several challenges remain, including non-specific uptake by unintended tissues, potential aggregation, and suboptimal biodistribution. Further refinements in nanocarrier design are necessary to enhance targeting specificity and minimize unintended side effects.

Another major challenge is determining appropriate dosing regimens to achieve maximum therapeutic efficiency with the lowest possible dosage and minimal adverse effects. Researchers are actively working on modifying nanoparticle surfaces with targeting ligands, which facilitate receptor-mediated endocytosis. This strategy enhances delivery efficiency, reduces required doses, and limits off-target interactions. Additionally, nanoparticle-based systems must undergo rigorous biocompatibility assessments to ensure their safety, particularly in chronic conditions like diabetes. The potential for immune responses triggered by synthetic oligonucleotides or nanocarriers further underscores the need for comprehensive preclinical evaluation before advancing to human trials.

Discussion

The hypothesis that a dual-miRNA therapeutic approach targeting miR-21 and miR-126 will restore endothelial function in diabetic vascular disease presents a promising strategy for mitigating the long-term vascular complications associated with diabetes. miR-21 is widely recognized for its pro-inflammatory and pro-fibrotic effects, while miR-126 is essential for maintaining vascular integrity and promoting endothelial repair. By simultaneously inhibiting miR-21 and replenishing miR-126, this approach seeks to counteract the detrimental effects of hyperglycemia-induced endothelial dysfunction. The proposed nanoparticle-based delivery system further enhances the therapeutic potential by ensuring targeted delivery and stability of these miRNAs within endothelial cells.

Recent studies indicate that miRNA dysregulation plays a significant role in diabetic vascular complications, with miR-21 overexpression contributing to endothelial inflammation and fibrosis, and miR-126 suppression impairing vascular repair. Correcting this imbalance has been shown to improve endothelial function and promote vascular regeneration. This aligns with emerging research demonstrating that targeting microRNAs involved in endothelial dysfunction can enhance endothelial health and reduce vascular complications. Furthermore, integrating the concept of miRNA with advanced nanoparticle delivery technologies could improve the precision and efficacy of RNA-based therapeutics, reducing systemic side effects.

However, the endothelial microenvironment is a highly complex and dynamic system, where multiple signaling pathways interact to regulate vascular function. While dual-miRNA therapy offers a promising strategy, it is crucial to consider potential unintended consequences. For instance, miR-21 also plays a role in tissue repair and immune regulation, raising concerns about possible off-target effects of its inhibition. Similarly, while restoring miR-126 is beneficial for vascular health, its overexpression in non-target tissues may lead to undesired angiogenic effects. A deeper understanding of the downstream molecular pathways affected by this approach is necessary to optimize its safety and efficacy.

Another critical challenge is the efficient and selective delivery of miRNA therapeutics to endothelial cells without affecting off-target tissues. Nanoparticle-based delivery systems, such as lipid nanoparticles or polymeric carriers, offer a potential solution by enhancing the stability and targeting efficiency of miRNA therapeutics. The use of endothelial-specific ligands or modified delivery vehicles could further improve selectivity, minimizing systemic exposure and potential toxicity. Additionally, exploring combination strategies with existing therapies, such as anti-inflammatory agents or RAAS inhibitors, may yield synergistic effects, providing a more comprehensive approach to managing diabetic vascular disease.

Future studies should focus on optimizing miRNA dosing, refining delivery mechanisms, and conducting in vivo validation in diabetic models to assess long-term efficacy and safety. If successful, this approach could pave the way for precision RNA-based therapies in cardiovascular medicine, offering a novel and more targeted strategy for addressing endothelial dysfunction in diabetes.

Conclusion

In conclusion, the dual-miRNA therapeutic approach targeting miR-21 and miR-126 holds great potential and should be considered as a solution for restoring endothelial function in diabetic patients. By counteracting the pro-inflammatory and fibrotic effects of miR-21 while enhancing the pro-reparative role of miR-126, this intervention aims to address a critical gap in current treatments for diabetic vascular disease. While the potential benefits are substantial, further research is necessary to optimize miRNA delivery, minimize off-target effects, and fully understand the long-term impact of this approach. With continued exploration and clinical validation, miRNA modulation could become a key component in improving vascular health and reducing the burden of diabetic complications.

About Me

Hey! I am Deena Farrukh, a grade 10 student exploring genomics and how we can use it to tackle cardiovascular diseases. If you have any questions or would like to connect, feel free to contact me via email or LinkedIn:

• Email: farrukhdeena@gmail.com
• LinkedIn: https://www.linkedin.com/in/deena-farrukh-94701b337/

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9. Nemecz, Miruna, et al. “Role of MicroRNA in Endothelial Dysfunction and Hypertension.” Current Hypertension Reports, vol. 18, no. 12, 11 Nov. 2016, link.springer.com/article/10.1007/s11906–016–0696–8, https://doi.org/10.1007/s11906-016-0696-8.

10. Pishavar, Elham, and Javad Behravan. “MiR-126 as a Therapeutic Agent for Diabetes Mellitus.” Current Pharmaceutical Design, vol. 23, no. 22, 13 Sept. 2017, https://doi.org/10.2174/1381612823666170424120121.

11. Qu, Mei-Jie, et al. “MicroRNA-126 Is a Prospective Target for Vascular Disease.” Neuroimmunology and Neuroinflammation, vol. 5, no. 4, 9 Apr. 2018, pp. 10–10, www.oaepublish.com/articles/2347-8659.2018.01, https://doi.org/10.20517/2347-8659.2018.01.

12. Rawal, Shruti, et al. “Down-Regulation of Proangiogenic MicroRNA-126 and MicroRNA-132 Are Early Modulators of Diabetic Cardiac Microangiopathy.” Cardiovascular Research, vol. 113, no. 1, 1 Jan. 2017, pp. 90–101, academic.oup.com/cardiovascres/article/113/1/90/2628083, https://doi.org/10.1093/cvr/cvw235.

13. Ring, Andrew, et al. “MicroRNAs in Peripheral Artery Disease: Potential Biomarkers and Pathophysiological Mechanisms.” Therapeutic Advances in Cardiovascular Disease, vol. 16, Jan. 2022, p. 175394472210969, https://doi.org/10.1177/17539447221096940.

14. Roy, Dipayan, et al. “MicroRNA 21 Emerging Role in Diabetic Complications: A Critical Update.” Current Diabetes Reviews, vol. 16, 3 May 2020, https://doi.org/10.2174/1573399816666200503035035.

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Author’s Note

Thank you for taking the time to read my research proposal on utilizing a dual microRNA therapy to combat endothelial dysfunction, a key driver of diabetic vascular disease. Throughout this process, I had the opportunity to dive deep into scientific literature, connect insights from epigenetics and vascular biology, and develop a hypothesis that could contribute to advancing cardiovascular medicine. Writing this article felt like stepping into the shoes of a scientific researcher, an experience that has been both challenging and incredibly rewarding!

This journey has strengthened my ability to synthesize complex information, extract key findings from research papers, and structure my ideas into a cohesive proposal. I am especially grateful for the wealth of publicly available scientific resources that have enabled me to explore and refine my understanding of this field. Without the contributions of researchers dedicated to expanding our knowledge, this project would not have been possible.

I appreciate your time and interest in this work, and I look forward to continuing my efforts in cardiovascular genetics. Stay tuned for future research and innovations!

Abstract

Cardiovascular diseases (CVD) remain a leading cause of global mortality, despite significant advancements in prevention and management. Traditional risk prediction models, while valuable, often fail to capture individual variability in disease susceptibility, underscoring the need for innovative tools. Polygenic risk scores (PRS) offer a novel approach by quantifying genetic predisposition through the aggregation of multiple genetic variants identified via genome-wide association studies (GWAS). This review explores the development, biological insights, and clinical implications of PRS for CVD.

Key findings highlight how PRS illuminate underlying biological pathways such as lipid metabolism and inflammation, enabling refined risk stratification for conditions like coronary artery disease, atrial fibrillation, and hypertension. Challenges, including population biases in GWAS and the integration of PRS with traditional clinical models, are discussed alongside strategies for improvement, such as leveraging diverse datasets and advancing machine learning applications.

Future directions emphasize expanding PRS utility through population screening, equitable healthcare implementation, and broader applications in other medical domains. By addressing current limitations and fostering innovation, PRS have the potential to transform personalized medicine, bridging genetic discovery with actionable clinical insights.

Table of Contents

Introduction

Part I: Genetic Foundations of Cardiovascular Risk

• 1.1 Monogenic vs. Polygenic Inheritance
• 1.2 Genome-Wide Association Studies (GWAS)

Part II: Development of Polygenic Risk Scores

• 2.1 Conceptual Framework for PRS Development
• 2.2 Data and Standardization Requirements
• 2.3 Performance Metrics

Part III: Biological Insights from PRS for Cardiovascular Diseases

• 3.1 Biological Pathways and Key Genetic Loci
• 3.2 Cardiovascular Phenotypes: Risk Stratification and Preventive Strategies

Part IV: Challenges in PRS Research and Application

• 4.1 Population Bias and Equity Issues
• 4.2 Integration with Traditional Risk Models

Part V: Future Directions of PRS

• 5.1 Advancing Population Screening
• 5.2 AI and Polygenic Risk Scores

Discussion

Sources

Introduction

Cardiovascular diseases accounts for 17.9 million deaths annually, according the the World Health Organization. This number represents the significant burden on healthcare systems globally, encompassing not only medical costs but also economic productivity losses and reduced quality of life for patients and families. Despite efforts to manage modifiable risk factors such as hypertension, diabetes, and smoking, the prevalence of CVDs remain incessantly high, especially in less-developed countries.

Although traditional risk prediction models, like the Framingham Risk Score exists, it fails to capture the full spectrum of individual variability in disease susceptibility. For instance, individuals with similar lifestyle pattern may exhibit different cardiovascular outcome, underscoring the need for innovative tools that consider the underlying genetic predisposition due to hereditary factors or even mutations.

Polygenic Risk Scores, a significant scientific breakthrough, offers a novel framework for quantifying genetic susceptibility to a particular disease or trait by aggregating the effects of multiple genetic variants associated with the condition. The relevance of PRS to cardiovascular risk stratification lies in its ability to complement conventional risk factors, enabling more precise identification of individuals at high genetic risk who might benefit from targeted prevention strategies. By implementing this tool into clinical practices, PRS could transform the current approach to CVD prediction, by bridging the gap between genetic discovery and actionable health insights.

This review paper aims to unravel the science behind PRS, explaining their development, underlying biological insights, and clinical implications. The current challenges and future direction to enhance the tool’s utility, accuracy, and equity in healthcare systems is also addressed.

Part I: Genetic Foundations of Cardiovascular Risk

The genetic foundations of cardiovascular diseases lie in both monogenic and polygenic variants as wells as genome-wide association studies (GWAS), that play an important role in identifying common variants.

1.1 Monogenic vs. Polygenic Inheritance

Understanding the genetic underpinnings of cardiovascular diseases (CVD) involves examining two primary modes of inheritance: monogenic and polygenic. These represent distinct patterns of genetic contributions, each with unique clinical and research implications. A polygenic disease refers to a genetic disorder that is caused by the aggregation of the impact several genes have on an individual. Conversely, monogenic diseases is the result of a singular genetic variation.

Monogenic Inheritance

Monogenic inheritance involves rare (minor allele frequency <1%, defined as the frequency of the second most common allele that occurs within a selected population), high penetrance mutations in single genes that are sufficient to significantly elevate the risk of CVD in affected individuals [1]. These mutations typically follow Mendelian patterns of inheritance (dominant, recessive, or X-linked) and are associated with well characterized disorders [1].

One of the most studies examples of monogenic CVD is familial hypercholesterolemia (FH), a disorder caused by mutations in the LDLR, PCSK9, and APOB genes. FH leads to markedly elevated low-density lipoprotein cholesterol (LDL-C) levels due to impaired clearance of LDL particles, resulting in premature atherosclerosis and increased risk of coronary artery disease (CAD). FH leads to early-onset CVD due to significantly elevated cholesterol levels. Key features of monogenic CVD include:

• High Penetrance: Individuals carrying mutations often display the related phenotype. To illustrate, heterozygous FH carriers have a 50% likelihood of passing the mutation to their children, and their lifetime risk of developing CVD can be 2–3 times higher than the general population.
• Early Onset: Clinical symptoms, such as myocardial infarction or angina, often occur earlier in life, necessitating early detection and intervention.

Despite their clinical importance, monogenic disorders account for only a small proportion of total CVD cases, with estimates suggesting they affect less than 1% of the population. Their limited prevalence highlights the need to study more complex genetic contributions.

Polygenic Inheritance

Unlike monogenic inheritance, polygenic inheritance reflects the combined effects of numerous genetic variants. It is a trait influenced by more than one gene. These variants, typically common in the population (minor allele frequency >1%), contribute to cardiovascular traits such as lipid levels, blood pressure, and inflammation. Polygenic inheritance is best described in terms of cumulative risk as it is quantitively distinct from Mendelian inheritance. Polygenic risk involves complex interactions as it includes both genetic and environmental factors, making it challenging to predict and manage.

A defining feature of polygenic inheritance is the small effect size of individual variants. Single nucleotide polymorphisms (SNPs) associated with CVD often have odds ratios (ORs) ranging from 1.01 to 1.2. Odds ratio is a statistical measure that quantifies the strength of associations between two event, which is the possibility that an outcome will occur in an exposed group, compared to a non-exposed group. For example, a variant near SORT1, which is a gene that regulates the LDL receptor expression, has been shown to modestly impact LDL cholesterol levels. Similarly, variants in APOE modulate cholesterol transport and metabolism, contributing incrementally to CVD risk. While the impact of each variant is diminutive, their collective contribution can be substantial, especially when numerous variants are aggregated into a polygenic risk score (PRS).

Polygenic inheritance is particularly significant in explaining the heritable component of CVD risk at the population level. Unlike monogenic disorders, which are rare and confined to specific families, polygenic risk is widespread, following a normal distribution in the population. This allows for stratification into categories of low, intermediate, and high genetic risk. Genome-wide association studies (GWAS) have identified over 200 loci associated with coronary artery disease (CAD), which collectively account for approximately 15–20% of the heritability of the disease. While this figure highlights the complexity of CVD genetics, it also underscores the importance of polygenic inheritance in developing predictive tools like PRS.

Understanding polygenic inheritance is crucial for public health and clinical practice, as it provides insights into population-wide risk profiles and enables the design of predictive tools tailored to diverse genetic backgrounds. By incorporating the cumulative effects of numerous common variants, researchers can refine risk stratification and improve early prevention strategies for individuals at varying levels of genetic susceptibility [1].

Comparing Monogenic and Polygenic Contributions

While monogenic inheritance provide critical insights about severe single-gene mutations, polygenic inheritance shows common SNPs that contribute to the small incremental risk of developing CVDs.

1.2 Genome-Wide Association Studies (GWAS)

Genome-Wide Association Studies (GWAS) has been instrumental in unraveling the genetic makeup of complex diseases, namely CVDs. GWAS analyze millions of genetic variants across genomes of large cohorts to identify single nucleotide polymorphisms that occur more frequently in people with a certain disease or trait. Although GWA studies are effective at identifying genetic locus-trait associations, they cannot be used be used alone to determine the genetic liability for a given trait in a genome of interest [4]. The findings from GWAS serve as the building blocks for developing polygenic risk scores (PRS), which cluster the effects of multiple SNPs to quantify one’s genetic predisposition to CVD.

Linking GWAS to Cardiovascular Risk

GWAS have revealed that most of the genetic risk for CVD arises from common variants with small effect sizes, each contributing marginally to disease risk. With this said, polygenic scores are now being used clinically. across biobanks and returned through direct-to-consumer testing platforms. GWAS findings of SNPs in the SORT1 gene or the APOE gene for example, are now consistently weighted in PRS for CVDs where numerous variants across diverse biological pathways collectively drive susceptibility.

While the advances in the predictive capacity of polygenic risk scores have been evident since the past decade, score performance remains quite low than the theoretical maximum, the proportion of trait liability by common DNA variants, particularly among individuals of non-European ancestry. Rather, polygenic scores integrating GWAS data from individuals of diverse backgrounds alongside the target population show improvement in predictive accuracy compared with methods only incorporating data from a single ancestry source.

How GWAS Inform PRS Development

The role of GWAS in PRS development is multifaceted, providing the necessary data for SNP selection, effect size estimation, and model construction:

1. SNP Identification:
   GWAS identify SNPs significantly associated with CVD risk, often uncovering hundreds of loci per study. These SNPs, ranked by their statistical significance (e.g., p-values) and effect sizes (e.g., odds ratios), form the pool of candidates for PRS construction.
2. Effect Size Estimation:
   For each SNP, GWAS estimate how much the allele contributes to the disease or trait. These effect sizes are then used as weights in PRS calculations, allowing for the aggregation of risk across multiple variants.
3. Biological Validation:
   GWAS findings often align with known biological mechanisms, enhancing the interpretability of PRS. For example, loci involved in lipid metabolism or inflammation provide insights into the pathways driving CVD, ensuring that PRS models capture biologically relevant risks.

Advantages of GWAS in PRS Development

• High Resolution: GWAS analyze millions of SNPs across the genome, enabling the identification of both known and novel loci associated with CVD. This comprehensive approach ensures that PRS reflect the full spectrum of genetic contributions.
• Population-Wide Utility: By aggregating small-effect variants identified in GWAS, PRS provide a continuum of risk applicable to the general population, distinguishing individuals at low, intermediate, and high genetic risk.
• Scalability: GWAS data can be used to develop PRS for specific cardiovascular phenotypes (e.g., CAD, atrial fibrillation), facilitating tailored applications in clinical and research settings.

Part II: Development of Polygenic Risk Scores

The creation and implementation of polygenic risk scores (PRS) for cardiovascular diseases involve leveraging genetic data to quantify an individual’s predisposition to disease. This process heavily relies on translating the information collected from GWAS into actionable scores, guided by a clear conceptual framework, robust datasets, and performance metrics used to validate their clinical utility.

2.1 Conceptual Framework for PRS Development

The foundation of PRS development lies in the aggregation of genetic information across multiple loci to capture the cumulative effects of common, yet trivial genetic variants associated with diseases risk. As mentioned previously, genetic variants are identified through GWAS are selected based on their statistical association with traits such as coronary artery disease (CAD), hypertension, or myocardial infarction. Once identified, these SNPs are weighted by their effect sizes, reflecting the magnitude of their contribution to disease.

The PRS is calculated by summing the weighted contributions of risk alleles carried by an individual. To further expand on this, each gene has two copies (alleles) that are present in pairs at each chromosomal locus and inherited from each parent. The several gene combinations that can produce different traits are accountable for the expressiveness of each trait in the body. To identify individuals with SNPs of interest, researchers calculate the frequency of alleles by dividing the number of individuals with the disease being studied by the total number of individuals in the cohort for the genotyping experiment. Then weights are assigned to each SNPs based on their effect size, determining the strength of the association between the SNPs and the trait or disease. A positive effect size indicates that a specific allele is linked to an increased risk of developing the trait or disease, while a negative effect size signifies that a specific allele is attributed to a lower risk. So, if an allele contributes to a heightened risk for the trait, it would be referred to as the risk allele. To calculate the weighted Polygenic Risk Score, the process involves multiplying the number of risk alleles for each SNP by the effect size that each of those risk alleles has. The total is then obtained by summing the total of these products across all the chosen SNPs and dividing each SNP’s impact size by the number of risk alleles a person carries for each SNP. This results in a genetic score for the specific disease being evaluated. A higher PRS reflects a greater genetic predisposition to the trait, while a lower PRS indicates a reduced genetic risk [7].

Social and environmental factors influencing PRS performance

It is essential to recognize that the PRS is only one component of genetic risk. Environmental and behavioral elements should also be considered. These include smoking, diet, physical activity, and even exposure to air pollution. Furthermore, risk factors and complex diseases are influenced by the conditions in which populations live in, known as the social determinants of health (SDOH). SDOH encompass an individual’s social and economic position, including access to healthcare resources, and reflect experiences of social exclusion, such as racism. For the effective development and application of PRS in CVDs, there is an urgent need to establish a conceptual framework that specifies relationships between PRS and external risk factors [6].

2.2 Data and Standardization Requirements

The development of reliable PRS directly depends on access to high-quality genetic data and the implementation of standardization practices to ensure accuracy and fairness. GWAS datasets form the foundation of PRS construction. These studies, such as those conducted by the UK Biobank, provide large-scale genomic data linked to well-characterized phenotypes. The reliability of PRS is inherently tied to the size and quality of these datasets, as they determine the robustness of SNP selection and weighting.

Although polygenic scores are a useful tool especially for personalized healthcare, scores calculated in a clinical setting should be valid for a single target sample and thus need to be constructed using a reference-standardized framework. Typically what happens is that a polygenic score is independent of and properties specific to the target sample, including the genetic variation available, and the linkage disequilibrium (LD) and minor allele frequency (MAF) estimates. In a reference standardized approach, the genetic variants considered can be standardized by using only single nucleotides polymorphisms that are commonly available after imputation, such as variation within the HapMap3 reference. The LD and MAF estimates can be standardized by using an ancestry matched individual-level genetic dataset such as 1000 Genomes. In this case, LD quantifies how often alleles at different loci occur together compared to their individual frequencies. Determining these properties (SNPs, LD, MAF) in reference data provides a practical approach for estimating polygenic scores for an individual, making them comparable to polygenic scores for other individuals of the same ancestry. Use of a reference-standardized framework also offers advantages by improving the comparability of polygenic scores across cohorts. Several polygenic scoring methods now recommend the use of HapMap3 SNPs and precomputed external LD estimate references, in line with a reference-standardized approach [10]

Standardization practices are imperative for the consistent application of PRS across populations. Additionally, including rare variants identified through whole-genome sequencing can also enhance the predictive power of PRS, particularly in individuals with strong familial histories of CVD. By meeting these data and standardization requirements, PRS can deliver equitable and accurate risk assessments across diverse populations.

2.3 Performance Metrics and Validation

The clinical utility of PRS depends on their ability to accurately predict cardiovascular outcomes, which is evaluated through rigorous performance metrics and validation processes.

The net reclassification improvement (NRI) metric assesses how effectively PRS improve upon existing risk models, such as the Framingham Risk Score or ASCVD calculator. NRI measures the proportion of individuals who are correctly reclassified into higher or lower risk categories when PRS are added to traditional models. This metric underscores the added value of PRS in enhancing clinical decision-making. Moreover, validation across independent cohorts is crucial to confirm the power of PRS. Ethnically diverse validation datasets are particularly important because performance often declines in populations that were underrepresented in the training data [12].

Part III: Insights from PRS for Cardiovascular Diseases

Through the aggregation of effects of numerous genetic variants, PRS not only quantify individual risk but also shed light on the biological pathways driving disease and enable targeted risk stratification across different cardiovascular phenotypes. This section explores how PRS illuminate key biological mechanisms and their utility in refining risk stratification and informing preventive strategies.

3.1 Biological Pathways and Key Genetic Loci

PRS for CVD are rooted in the cumulative contributions of genetic variants identified through GWAS. These studies have unearthed hundred of loci associated with cardiovascular traits, many of which map to gene involved in biological pathways such as lipid metabolism, inflammation, and vascular function. These pathways play crucial roles in conditions such as coronary artery disease, myocardial infarction, and hypertension [12].

Lipid metabolism is central to atherosclerosis and coronary artery disease. Variants near the SORT1 locus (1p13) influence LDL receptor activity, regulating plasma LDL cholesterol levels. Similarly polymorphisms in the APOE locus (19q13), such as the ε4 allele, contribute to higher LDL-C and increased CVD risk. Variants in the LPA locus (6q26) have an affect on lipoprotein levels, which is linked to atherogenesis and arterial plaque formation. These loci are consistently weighted in PRS models, underscoring their importance in CVD development.

3.2 Cardiovascular Phenotypes: Risk Stratification and Preventive Strategies

The genetic variants associated with cardiovascular phenotypes, including coronary artery disease, myocardial infarction, atrial fibrillation, hypercholesterolemia, PRS can differentiate individuals at varying levels of genetic predisposition. It can offer insights into disease-specific risks and guiding preventive strategies tailored to each phenotype.

Coronary Artery Disease and Myocardial Infarction
PRS for coronary artery disease, one of the most extensively studied cardiovascular phenotypes, integrate SNPs associated with lipid metabolism and inflammation. GWAS of CAD in the general population has shown that common genetic variation also influences the risk for CAD. Interestingly, 167 separate genomic loci have been identified that are significantly associated with CAD. This could be very beneficial for asymptomatic middle-aged adults who are are at risk for developing a heart related disease. If they end up doing polygenic risk score testing, and get a high CAD PRS, more intensive and earlier efforts for lifestyle modifications and therapies could be prompted [1].

“PRS testing gives us a very good picture of risk of these polygenic diseases and is most valuable in younger people… PRS for coronary artery disease is most useful for people who are under 50 years old.” — Dr. Ernst J. Schaefer, MD Chief Medical Officer and Laboratory Director of Boston Heart Diagnostics

For myocardial infarction (MI), PRS highlight the role of loci like 9p21, which affects vascular integrity and inflammatory responses. These insights are critical for early detection and intervention, especially in younger individuals or those with ambiguous traditional risk profiles. High-risk individuals identified by PRS may benefit from lifestyle changes such as smoking cessation, as well as pharmacological interventions like statins.

Atrial Fibrillation

AF is a recognized independent risk factor for stroke and it can contribute to heart failure. The prevalence of this diseases typically increases with age and it commonly coexists with other cardiovascular diseases. The growing number of common genetic variants linked to atrial fibrillation has facilitated the development of AF Polygenic Risk Scores. Recent advances in statistical methods, particularly the inclusion of a broader range of Single Nucleotide Variants (SNVs) in PRSs, have further enhanced their predictive accuracy. These improvements have bolstered risk prediction in two key ways: by increasing the accuracy of AF prediction in the absence of clinical risk factors and by improving prediction when combining PRSs with clinical risk factors [1].

Beyond predicting AF itself, AF PRSs may also help forecast complications associated with AF, such as ischemic stroke. Studies have revealed a genetic basis between AF and ischemic stroke, with loci at the PITX2 and ZFHX3 genes linked to the risk of both conditions. Several AF PRSs have been shown to predict stroke risk, while ischemic stroke PRSs demonstrate predictive power specifically for strokes in patients with AF. However, early investigations into the use of PRSs for predicting AF recurrence remain inconclusive, highlighting the need for larger studies to determine their potential role in this context [1].

Hypertension

PRS for hypertension leverage genetic variants influencing blood pressure regulation, including SNPs in AGT (angiotensinogen) and ACE (angiotensin-converting enzyme) [13]. High-risk individuals identified through PRS can benefit from early lifestyle interventions, such as sodium reduction, weight management, and exercise. Pharmacological approaches, including ACE inhibitors or angiotensin receptor blockers, may also be initiated earlier in those with a genetic predisposition, even before clinical hypertension is diagnosed.

Part IV: Challenges in PRS Research and Application

Polygenic Risk Scores (PRS) for cardiovascular diseases (CVD) hold immense potential for improving risk prediction and guiding preventive strategies. However, significant challenges remain in their development, application, and validation. These challenges include population biases that restrict their equity and generalizability and issues with predictive power that impact their integration with clinical models. Addressing these hurdles is imperative to realizing the full potential of PRS in clinical practice and ensuring that they benefit diverse populations equitably.

4.1 Population Bias and Equity Issues

A major limitation in PRS research is the overrepresentation of individuals of European ancestry in GWAS, which serves as the basis for PRS. According to a 2016 analysis, approximately 81% of GWAS participants were of European descent, while individuals of African, Asian, and other ancestries remain significantly underrepresented. This lack of diversity creates inequities in PRS accuracy and limits their applicability across populations as it only is being of benefit merely to “a privileged few” [14].

Population Bias in GWAS Data

GWAS findings depend on allele frequencies and linkage disequilibrium (LD) patterns, both of which vary across populations. SNPs identified as significant in one ancestry group may have different effect sizes or frequencies in another. To illustrate, PRS derived from European GWAS datasets have been show to perform poorly in individuals of African ancestry. A common example of this is when algorithms help a doctor to prescribe the right amount of dosage of warfarin (blood-thinner) or a patient work effectively for people with European genes, but far less accurate for African Americans [15].

Equity Issues in PRS Application

The disparities in PRS performance have real-world consequences in cardiovascular care. For example, an individual of African descent may be misclassified into a lower-risk category for coronary artery disease based on a European-derived PRS, potentially delaying necessary preventive measures. Conversely, overestimation of risk can lead to unnecessary treatments or anxiety. These injustices highlight the urgent need for diverse representation in GWAS and PRS validation studies.

Addressing Population Bias and Promoting Equity

Efforts to address these biases include increasing the diversity of GWAS datasets through initiatives like the All of Us Research Program and the Human Genome Diversity Project, which aim to create diverse health databases and promote research on human genetic diversity. Multi-ancestry GWAS that incorporate genetic data from diverse cohorts improve the accuracy of PRS across populations. Developing ancestry-specific PRS models that adjust for population differences can further enhance equity in PRS applications.

Ultimately, equitable implementation of PRS in CVD care requires not only technical advancements but also ethical considerations to ensure that all populations benefit from genomic medicine.

4.2 Predictive Power and Integration with Clinical Models

Polygenic risk scores represent a promising tool for improving risk prediction in cardiovascular diseases (CVD), but their utility becomes most impactful when integrated with established clinical models. Clinical models such as the Framingham Risk Score (FRS) and the ASCVD Risk Calculator are widely used in cardiovascular care to assess a patient’s risk of developing conditions like CAD or stroke. These models incorporate traditional risk factors, including age, cholesterol levels, and blood pressure, to create informed decisions about preventive interventions like statins or lifestyle changes.

PRS complement these models by adding a genetic dimension to risk assessment, which is particularly valuable in cases where traditional factors are insufficient.

The graph above represents the enhanced predictive accuracy of polygenic risk scores with clinical risk tools, compared to clinical risk tools alone. The clinical models that were used primarily included variables such as age, smoking status, diabetes, and a history of cardiovascular diseases. The integration of PRS with the specified tool for each disease had significantly increased the predictive accuracy [1].

As efforts to integrate PRS with clinical models progress, these combined approaches have the potential to revolutionize cardiovascular care by delivering more precise and personalized risk assessments.

Part V: Future Directions of Polygenic Risk Scores

Polygenic risk scores (PRS) are poised to transform healthcare by enabling earlier identification of disease risk, tailoring preventive strategies, and informing therapeutic decisions. The implementation of AI models in PRS as well can further improve the prediction analysis of this tool. While challenges like population bias and integration hurdles remain, significant progress is being made to address these limitations. Looking forward, PRS has the potential to revolutionize population-level screening and equity in genetic healthcare while expanding its applications across diverse medical fields.

5.1 Advancing Population Screening

The integration of PRS into population-level screening initiatives marks a turning point in precision medicine. Screening programs already use PRS for cardiovascular diseases (CVD) to identify high-risk individuals, offering preventive interventions before clinical symptoms manifest. For example, UK Biobank data has been instrumental in demonstrating the predictive utility of PRS for CAD, with individuals in the left side of the bell curve of PRS showing a significantly elevated risk. Genetic testing companies such as 23andMe provide polygenic risk scores in their genetic reports and they are available for direct-to-consumer testing, allowing individuals to see their estimated likelihood of developing a certain health condition [16].

Improving Population Screening
The future of PRS in population screening lies in refining its accuracy, scalability, and accessibility. For instance, integrating PRS into screening for atrial fibrillation or stroke could enable earlier monitoring for arrhythmic events. These developments pave the way for PRS to be used alongside traditional screening tools, enhancing their predictive power and utility.

Implementing the Use of Polygenic Risk Scores in Clinical Settings
Polygenic risk scores (PRS) focus on prevention, providing individuals with the opportunity to take proactive steps toward mitigating health risks. Individuals positioned at the extremes of the PRS distribution require prompt and targeted interventions to address their heightened risk. On average, polygenic risk testing costs between $100 and $250, with limited coverage by most health insurance plans. Despite these financial barriers, PRSs hold significant potential to improve longevity and enable proactive health management within clinical settings.

However, effective integration of PRSs into clinical practice necessitates careful consideration of their interpretation and application by both physicians and patients. For example, in the case of a high PRS for atrial fibrillation (AF), prescribing unnecessary medications or therapies could introduce avoidable risks. Instead, PRS results could serve as a powerful motivational tool to encourage patients to adopt healthier dietary and lifestyle behaviors.

To realize the full potential of PRSs in preventative care, it is imperative to establish clear guidelines for primary care physicians. As key providers in preventative medicine, they require robust frameworks for interpreting PRS data and translating it into actionable clinical strategies. Developing these guidelines will ensure that PRSs are utilized safely and effectively to enhance patient outcomes and support personalized healthcare [16].

5.2 AI and Polygenic Risk Scores

With some recent breakthroughs in AI, it can play a pivotal role in enhancing the development of polygenic risk scores by determine which genetic variants are most predictive of disease risk. Machine learning (ML) algorithms can analyze large-scale genomic data from diverse populations to identify polymorphisms most strongly associated with specific diseases. By leveraging the growing availability of medical big data, AI enables the creation of patient-specific models to improve cardiovascular disease (CVD) diagnosis, intervention, and outcomes. Advanced techniques, such as neural networks and deep learning (DL) algorithms, can integrate genetic variations into comprehensive PRS models. Additionally, AI can refine the weighting of genetic variants by considering their effect sizes, gene-gene interactions, and environmental influences, resulting in more precise and individualized risk assessments. AI can also develop sophisticated risk stratification tools that account for multiple factors and their interactions, enabling tailored risk assessments and preventative strategies for individuals based on their genetic makeup and environmental exposures. By accelerating PRS model development and enhancing their applicability across diverse populations, AI supports the creation of accurate and personalized risk models. These models can inform therapeutic decision-making and guide targeted screening and prevention efforts, such as recommending earlier and more frequent screenings for high-risk individuals while minimizing unnecessary interventions for those at low risk [7].

Discussion

Polygenic risk scores (PRS) represent a paradigm shift in cardiovascular risk prediction, complementing traditional models by integrating genetic insights. This review underscores their ability to provide nuanced stratification of genetic risk, particularly for conditions like coronary artery disease and atrial fibrillation. The ability of PRS to aggregate small-effect genetic variants into a cumulative score offers unique advantages in identifying individuals at elevated risk, even in the absence of conventional risk factors.

Despite their promise, significant challenges hinder the widespread adoption of PRS. Population biases in GWAS datasets lead to inequities in PRS accuracy across ancestries, reducing their utility for non-European populations. Strategies to mitigate these biases, such as multi-ancestry GWAS and ancestry-specific models, are crucial for ensuring equitable healthcare outcomes. Additionally, the predictive power of PRS, while moderate, highlights the need for integrating rare variants and environmental factors to enhance accuracy.

The clinical implementation of PRS requires careful integration with established models like the Framingham Risk Score or ASCVD calculator. Combining PRS with traditional tools offers improved predictive power but introduces complexities in risk interpretation and communication. Establishing standardized protocols and training clinicians in PRS interpretation will be critical to overcoming these barriers. Future advancements in PRS will rely heavily on technological innovations, particularly in artificial intelligence (AI) and machine learning (ML). These tools can optimize PRS development by analyzing large-scale genomic datasets, refining variant weighting, and enabling dynamic, individualized risk models.

By addressing current limitations and embracing interdisciplinary approaches, PRS can revolutionize preventive care and therapeutic strategies. Their integration into clinical practice, guided by equity and innovation, promises to transform the landscape of personalized healthcare.

About Me

Hey! I am Deena Farrukh, a grade 10 student exploring genomics and how we can use it to tackle cardiovascular diseases. If you have any questions or would like to connect, feel free to contact me via email or LinkedIn:

• Email: farrukhdeena@gmail.com
• LinkedIn: https://www.linkedin.com/in/deena-farrukh-94701b337/

Sources

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Hypertension, which occurs when your blood pressure increases to unhealthy levels affects over one billion people worldwide, making it one of the most prevalent threats to global health. To put that into perspective, 1 in 4 people are affected by this condition. Known as the “silent killer” because of it being asymptomatic, hypertension often goes unnoticed until it is detected during a blood pressure check or when it contributes to related diseases like a heart attack or stoke. Alarming as it is, if left untreated, hypertension greatly raises the risk of cardiovascular, brain, and kidney diseases, and is responsible for nearly half of all deaths linked to heart disease and stroke worldwide.

At the center of this issue lies a critical enzyme known as angiotensin-converting enzyme (ACE or ACE1) which is produced by the ACE gene, is a key regulator of blood pressure within the body. Interestingly, variations in the ACE gene, like the ACE I/D polymorphism, can change how much of this enzyme is produced or its function as a whole. In this study, I will be depicting the ACE enzyme using AlphaFold to gain a better understanding of how the ACE I/D Polymorphism interacts with it and what that means for blood pressure and heart health. Through this, we can unlock exciting insights into the genetic factors of hypertension, paving the way for more precise, personalized approaches to treating cardiovascular diseases.

As discussed in my previous article on using genomics technologies to prevent cardiovascular diseases before its onset, there is numerous comprehensive case studies being done to connect the dots between genetic variants to our heart health. The field of cardiovascular genetics has untapped potential as it requires more awareness about this possibility!

Factors Causing Hypertension

So, what exactly results in hypertension?

Well, firstly, Essential Hypertension (EH), commonly referred to as hypertension, is a condition where your blood pressure is high for a prolonged period. It is one of the most common disorders affecting the heart and blood vessels. It is important to note that even moderately high blood pressure can increase your risk of developing heart diseases over the course of time.

As of now, the exact causes of hypertension remains unclear. However, it is typically attributed to factors such as one’s age, eating patterns, and level of physical activity as they all have a strong influence on your blood pressure. Other factors include smoking, stress, or having health concerns such as diabetes and high cholesterol. Additionally, hypertension frequently runs in families, highlighting genetic factors at play; children whose parents both have the disease can have a 46% chance of inheriting it, and approximately 60% of hypertensive patients report a family history. There are two primary types of heredity of hypertension: key gene dominant inheritance, where a variant in one copy of a gene is sufficient enough to drive the condition, and the polygene associated inheritance where multiple genes contribute to susceptibility. Genes associated with the renin–angiotensin system (RAS) and sodium regulation are all implicated in EH development, linking genetic makeup directly to blood pressure regulation.

Hypertension as a Global Health Crisis

Most of us are likely familiar with someone who has dealt with high blood pressure in the past. For me, I have seen my own parents members as well as immediate family members experiencing it. When we think of this in a global perspective, high blood pressure is a worldwide problem and the greatest impacts of it are being seen in South Asia, Sub-Saharan Africa, Latin America and the Caribbean, and East Asia and the Pacific. Interestingly, the prevalence of hypertension is much higher in low — and middle-income countries (31.5%) compared to high-income countries (28.5%). This directly connects to why only 1 in 3 people with hypertension are able to receive medical care and only one in ten individuals are able to keep their blood pressure at healthy levels in developing countries.

The economic burden this disease carries is substantial as well. Cardiovascular disease accounts for 20% of current total healthcare spending according to the “Global Brief on Hypertension”, done by the World Health Organization, and approximately 10% of it is used for managing hypertension and its complications. These statistics summons an urgent need for more funding and research needed to prevent the increase of hypertensive patients globally.

The Renin-Angiotensin Aldosterone System (RAAS) — Your Blood Pressure Regulator

It’s quite a long term, isn’t it? Well, RAAS is a complex hormonal pathway essential for regulating blood pressure and fluid balance in the body. The system starts off with the kidneys releasing renin (a type of enzyme), in response to low blood pressure. Renin acts on the protein angiotensinogen, converting it to angiotensin I, which is then transformed into angiotensin II by the enzyme ACE. Angiotensin II, is the primary hormone in this process as it raises blood pressure levels by causing the blood vessels to contract. In turn of this, aldosterone, another type of hormone is released from the adrenal glands, which increases thirst and salt cravings. Adrenal glands are located each on top of your two kidneys. Aldosterone then prompts the kidneys to retain more sodium and water, elevating blood volume and pressure. In a healthy RAAS, this mechanism adjusts itself to maintain normal blood pressure. However, in cases of hypertension, the system can become unable to process in moderation as it becomes overactive. This overactivity is caused by chronic stress, high salt intake, and genetic variations like the ACE I/D polymorphism.

What the ACE I/D Polymorphism Does

As mentioned previously, the Angiotensin-Converting Enzyme is a crucial component to RAAS. The levels of how much this enzyme is produced is controlled by heredity, that being the ACE gene. For more context, the gene is located on the human chromosome 17q23. It has a total length of 21KB and it consists of 26 exons and 25 introns. In other words, think of the ACE gene as a book with 21,000 letters (base pairs) being divided into 26 chapters (exons) that contain important information, separated by 25 intermissions or breaks (introns). The ACE Insertion/Deletion Polymorphism however, is a well studied variant of the ACE gene and it is located on the 16th intron. The variant is characterized by the presence (I) or absence (D) of a 287 bp Alu repeat sequence within that intron. An Alu repeat sequence in simple terms is highly repetitive DNA. This polymorphism results in three different genetic makeups (genotypes)-DD, II, and ID. These differences can influence the expression of the ACE gene, which in turn interact with the ACE enzyme, influencing bodily functions such as blood pressure regulation.

A larger majority of previous studies done on the impacts these genotypes have on ACE enzyme activity, unanimously say that individuals who carry the DD genotype (two D alleles) tend to have higher ACE activity, leading to increased conversion of Angiotensin I to Angiotensin II, resulting in higher blood pressure levels. One research paper suggested that increased ACE activity raises angiotensin II levels, which leads to cell growth and division by activating certain proteins and chemicals in the body. This process reduces the availability of nitric oxide, a molecule that helps blood vessels function properly, causing damage to the vessel lining. Additionally, it is also suggested that is adversely influences specific cardiovascular diseases, but appears to do so in specific geographical regions and in particular patient subgroups. Conversely, the II genotype (two I alleles) is linked to lower ACE enzyme activity when compared to the DD and ID genotypes. This results in potentially reduced conversion of angiotensin I to angiotensin II, which may be associated with lower chances of hypertension and other cardiovascular diseases.

Depicting the ACE Enzyme on AlphaFold

AlphaFold, developed by DeepMind, is a revolutionary AI program that is used to predict the 3D structure of biological molecules like proteins, ligands, DNA, RNA, and more. In terms of proteins, it uses amino acid sequences — the building blocks of proteins — to generate accurate structural models, addressing how their sequence determines their shape and function. Traditionally, modelling proteins was a laborious job; with AlphaFold, the process is accelerated allowing one to do it within minutes.

Step 1: Open up UniProt

UniProt is a resource used to access the protein sequence through their database. We will begin with typing in the name of our protein, which is the Angiotensin-converting enzyme. The first entry is the one that we will be using as the sequence is based off of homo sapiens, us humans! The amino acid sequence of this protein is lengthy as it is composed of 1,306 amino acids. The length of each protein varies as amino acids determine the complexity of it through the functions these proteins are able to perform.

Step 2: Insert the sequence on the AlphaFold Server

From this step forward, we will be transitioning onto the AlphaFold. Once the amino acid chain is copied, simply input the sequence into the protein entity. The process of the program being able to model the protein takes 5–10 minutes, so just hang in there!

Step 3: Interpret the 3-D structure of your protein

After 5 minutes, AlphaFold was able to depict the the ACE protein. Based off of the data it has provided us, we can interpret the results of our model.

To start off, the predicted template modelling (pTM) score shown at the top is 0.75. This shows that it was a fairly decent prediction. A pTM score above 0.5 means that the overall predicted fold accurately resembles the true protein structure. We can also see that four different colours are used to assess the accuracy of our complex. Dark blue, which has a confidence score of greater than 90% surrounds most of our protein. Moving forward, cyan which has a confidence level between 70–90% takes over a small portion of our protein as well. Yellow, with a confidence level of 50–70% is just a sliver of our protein. Lastly, orange which scores a confidence level of less than 50%, can mainly be seen at the two ends of the ACE protein.

At the right, there is a graph showing the scored residue compared to the aligned residue. This represents the predicted aligned error which is a measure of how confident AlphaFold is in the relative position of residues shown in the predicted protein. Residues are when two amino acids bond with each other. In the plot, the scored residue refers to the residue being evaluated for positional accuracy and seeing if they are binded correctly. On the other hand, the aligned residue is the one being compared to the chosen residue. For instance, if we take the scored residue of 1044 and compare it with the aligned residue of 783, the coordinate is found in a dark green square. This tells us that the positioning of the residue is highly accurate.

At the bottom of the plot is the expected position error (Ångströms). This represents the model’s predicted uncertainty about the relative position of residues in the protein structure. Ångströms is a unit of measurement used to measure diminutive distances like the ones in proteins. 1 Ångström unit is equal to 0.0000000001 meters.

A Bigger Picture of the ACE I/D Polymorphism at Play

Taken together, it can be deduced that the interaction between the ACE Insertion/Deletion Polymorphism and the DD-ACE genotype adversely influences specific cardiovascular diseases namely premature coronary artery disease, hypertension, and ischemic heart disease. However, based off of my findings from multiple research papers, the impact the DD genotype has appears to be small although it is considered as a factor of higher ACE enzyme activity. Since the renin-angiotensin aldosterone system is relatively complex, the ACE enzyme is only one component of the blood pressure regulation process. With that said, given the multifactorial nature of cardiovascular diseases, it is highly unlikely that one genetic polymorphism could exert a substantial effect independently. Rather, several other elements may be at play behind the scenes. This includes other genetic variants that we are unable to identify, environmental factors, and one’s lifestyle. Therefore, while the DD-ACE genotype may contribute to CVD and hypertension susceptibility, its influence is extremely limited, highlighting the need to consider the cumulative effects of multiple factors within the intricate genetic and physiological landscape. However, we can’t just lose hope here! In this case, further investigations of other polymorphisms within the ACE gene and their possible synergisms with traditional risk factors for CVD could help us create better solutions for CVD susceptibility.

My Takeaways from the David Barley Research Institute

Recently, I had the incredible opportunity to meet Dr. Guillaume Pare at the David Barley Research Institute of McMaster University. Dr. Pare is a Professor in the Department of Pathology and Molecular Medicine as well as Director of the Clinical Research Laboratory. He works in the field of cardiovascular genetics and he has previously done research on the ACE and ACE2 enzymes for Heart and Stroke Foundation.

During the couple of hours I spent at the institute, I attended an Academic Meeting with numerous doctors and PhD researchers. They presented their research about the roles genes play in cardiovascular diseases. Shortly after, Dr. Pare gave me a tour around his lab and I got to see groundbreaking genomic technologies like the Illumina Whole Genome Sequencer!! Be sure to stay tuned for my upcoming article if you are still curious about the details of this memorable experience!

In regards to the subject of this article, I asked Dr. Pare about his insights on the link between genetics and cardiovascular disease. He said that the field of cardiovascular genetics is fairly new and majority of the breakthroughs under this field of study occurred within the last 15 years. I also asked him about what his thoughts were on the impact the ACE I/D Polymorphism has on the ACE enzyme. His response was very similar to my findings. Dr. Pare proposed that the risk of heart disease is not just due to a single genetic mutation, but its hundreds, in fact thousands of weaker variants causing it. Cardiovascular diseases are a bit more intricate in the context of genetics. It is not like sickle cell anemia or cystic cell fibrosis that are caused by one genetic mutation (these are called mendelian diseases). With that said, the ACE I/D polymorphism is just one of many variants contributing to CVDs.

How the ACE I/D Polymorphism Could Help With Future Research

This variant of the ACE gene could help with future research in countless ways. The indication from scientific studies that show individuals with the DD genotype tend to have higher ACE levels, could guide more targeted treatment approaches. For example, people with the DD genotype may benefit from ACE inhibitors, enhancing the efficacy of hypertension treatment. Furthermore, this polymorphism could serve as a genetic marker for identifying those at a higher risk, aiding in early detection and intervention strategies. By focusing on such genetic markers, researchers may develop more personalized, effective therapies that reflect the unique genetic profile of each patient, ultimately improving hypertension management on a global scale and reducing associated health burdens.

Next Steps

As a project, I would like to further advance this study into something that can be replicated by a lab. To be able to do this, I would need to learn more about genotyping, where I use the polymerase chain reaction (PCR), a method that amplifies specific DNA sequences. In this context, PCR can distinguish between the insertion (I) and deletion (D) alleles by using fluorescent dyes to monitor the amplification process of the region of the ACE gene where this polymorphism occurs.

In addition to that, protein assays would need to be used to assess the activity or concentration of proteins encoded by genes. For the ACE enzyme activity, assays could measure the amount of ACE enzyme present in plasma or tissue samples by using antibodies that specifically bind to ACE. Differences in enzyme levels across different genotypes can provide insights into how genetic variations affect enzyme activity and potentially influence hypertension risk.

Together, these techniques can offer a comprehensive approach to understanding how genetic variations in the ACE gene can influence blood pressure regulation and potentially lead to hypertension

Here is a video version of my article:

TL;DR

I used AlphaFold to depict how the ACE enzyme looks like. I also studied the impact its variant, the ACE Insertion/Deletion Polymorphism has on blood pressure. To complement my findings, I had the opportunity to visit Dr. Guillaume Pare, who showed me the work being done in cardiovascular genetics.

Acknowledgements

I would like to express my gratitude to the availability of open-source platforms that helped me complete my research on the ACE enzyme and its variants. AlphaFold was invaluable for visualizing the protein structure, UniProt provided access to its amino acid sequence. A special thank you to Dr. Pare for allowing young innovators like me into your lab. Your guidance and willingness to answer my questions were crucial to the success of my project. Without Dr. Pare and these public resources, this research would not have been possible.

About Me

Hey! I am Deena Farrukh, a grade 10 student exploring genomics and how we can use it to tackle cardiovascular diseases. If you have any questions or would like to connect, feel free to contact me via email or LinkedIn:

• Email: farrukhdeena@gmail.com
• LinkedIn: https://www.linkedin.com/in/deena-farrukh-94701b337/

Luo, Zhi. “Impacts of ACE Insertion/Deletion Variant on Cardiometabolic Risk Factors, Premature Coronary Artery Disease, and Severity of Coronary Lesions.” Scientific Reports, vol. 14, no. 1, June 2024, https://doi.org/10.1038/s41598-024-64003-w.

Mills, Katherine T., et al. “Global Disparities of Hypertension Prevalence and Control.” Circulation, vol. 134, no. 6, Aug. 2016, pp. 441–50. https://doi.org/10.1161/circulationaha.115.018912.

Al, Berek Pius, et al. “Hypertension: A Global Health Crisis.” Annals of Clinical Hypertension, vol. 5, no. 1, July 2021, pp. 008–11. https://doi.org/10.29328/journal.ach.1001027.

— -. “Hypertension | What We Do | World Heart Federation.” World Heart Federation, 24 Aug. 2023, world-heart-federation.org/what-we-do/hypertension/#:~:text=It%20affects%20one%20billion%20people,risk%20factor%20for%20death%20globally.

World Health Organization. A Global Brief on Hypertension. 2013, iris.who.int/bitstream/handle/10665/79059/WHO_DCO_WHD_2021.2_eng.pdf?sequence=1.

Professional, Cleveland Clinic Medical. “Angiotensin.” Cleveland Clinic, 1 May 2024, my.clevelandclinic.org/health/articles/23359-angiotensin.

Mattu, Raj K., et al. “A DNA Variant at the Angiotensin-Converting Enzyme Gene Locus Associates With Coronary Artery Disease in the Caerphilly Heart Study.” Circulation, vol. 91, no. 2, Jan. 1995, pp. 270–74. https://doi.org/10.1161/01.cir.91.2.270.

Niu, Tianhua, et al. “Angiotensin Converting Enzyme Gene Insertion/Deletion Polymorphism and Cardiovascular Disease.” Drugs, vol. 62, no. 7, Jan. 2002, pp. 977–93. https://doi.org/10.2165/00003495-200262070-00001.

“Using Genetics to Beat Heart Attacks.” Heart and Stroke Foundation of Canada, www.heartandstroke.ca/articles/using-genetics-to-beat-heart-attacks.

Butler, R. “The DD-ACE Genotype and Cardiovascular Disease.” Pharmacogenomics, vol. 1, no. 2, May 2000, pp. 153–67. https://doi.org/10.1517/14622416.1.2.153.

How genomics could be used to prevent inherited heart disease among younger patients.

“Your father recently endured two silent heart attacks, and he is at risk of another,” the cardiologist explained, words that would leave anyone in utter disbelief. Imagine receiving such news without warning — it’s overwhelming to process. In this case, however, timely intervention through a complex procedure, known as a total occlusion, led to a successful recovery. This was me just barely a month ago, and it made me question if there were ways we could have addressed this situation earlier on before conditions had aggravated. Well, the emerging field of cardiovascular genetics provides promising answers to this question.

Cardiovascular diseases (CVDs) remain the leading cause of death worldwide, claiming approximately 17.9 million lives annually. According to a report by the World Health Organization, South Asians, who make up a quarter of the global population, account for over 50% of all cardiovascular-related deaths. This translates to around 8.95 million deaths each year, highlighting a disproportionate burden of heart disease within this ethnic group. These numbers are quite outrageous, and this especially raises concerns for the health of future South Asian generations. Although poor food choices, stresses, and lack of exercise come into play for this issue, many people in this demographic are also likely to inherit CVDs from their family. This is where genomics comes into play — from gene therapies to early detection and screening, this field can serve as a new hope for us to prevent the risk CVDs from occurring before they even start.

Status Quo: How Cardiovascular Disease is Currently Being Addressed

The current approach to how CVDs are being addressed in patients mainly relies heavily on traditional factors such as age, smoking, lifestyle, cholesterol levels, blood pressure, etc. This method of diagnosing is not very accurate since there could be a lot more underlying aspects that have not been taken into consideration. For high-risk patients surgical interventions like stents and bypass are common. However, speaking from what I have seen as a teen, there are a number of relatives I know who only got to learn that they have a CVD only after experiencing a heart attack or stroke.

When it comes to treatment, those who have high cholesterol or hypertension are often prescribed with medicines such as statins, beta-blockers, or ACE inhibitors, all of which target broad populations. While effective in many cases, these treatments don’t account for individual variations in how patients respond to drugs. In fact, some patients experience severe side effects from medications like statins due to genetic factors, while others see little benefit. Additionally, this “one-size-fits-all” approach fails to identify those who might be at high risk due to genetic factors but don’t exhibit obvious symptoms. As one can see, our bodies are really complex, so in order to take preventative measures for such diseases to arise, we must look into the building blocks of our bodies — what makes you, you! Our DNA.

How Genomics Could be a be a Game Changer

One promising avenue to tackle cardiovascular diseases before the symptoms even start to appear among South Asians lies in the use of Whole Genome Sequencing (WGS). It is a comprehensive method used for analyzing entire genomes — that being the entire set of DNA instructions found in a cell. Think of it as a code or a manual that has all the information needed for an individual to function. In us humans, the genome consists of 23 pairs of chromosomes found in the headquarters of the cell, the nucleus, as well as a small chromosome in the cell’s mitochondria. The genomic information that the WGS method collects is used for identifying inherited disorders, characterizing the mutations that drive cancer progression, and in our case, pinpoint genetic variants that contribute to cardiovascular diseases.

Why is WGS the solution? Genomics, and this technology specifically takes a rather proactive approach to heart disease. Instead of of having options that were pretty much limited to “watch and wait,” individuals can be informed of the risk in advance, enabling them to take measures like regular monitoring of the heart, lifestyle modifications, and and gene-editing techniques to prevent the onset. In terms of the South Asian demographic, unfortunately, they have higher rates of CVD and experience its negative effects of it at younger ages (under 40 years) when compared to other ethnic groups. This directly hints at why young adults, mainly South Asians should undergo Whole Genome Sequencing.

The Process of Whole Genome Sequencing (WGS)

The process begins with collecting a biological sample, this can be either be blood, bone marrow, or tissue, depending on the clinical context. Technicians then extract the DNA from the cells in the sample, then purify it, and suspend it in a liquid.

Library Preparation:

The extracted DNA is broken up into fragments typically ranging from 150 to 100,000 chemical base pairs long! The length of the DNA pieces directly correlate to the sequencing technology used. Special adapters are then attached to the ends of these DNA fragments, creating what is called a sequencing library. As a side note, the chemical bases are the four building blocks called nucleotides which make up a DNA: adenine (A), thymine (T), cytosine (C), and guanine (G). The nucleotides bond with one another (A with T, and G with C) to create chemical bonds known as base pairs, which link the two DNA strands.

Sequencing:

The prepared DNA library is loaded into a sequencing machine like Illumina or Oxford Nanopore. These machines read the sequence of nucleotides in each DNA fragment and determines the order of all 3 billion base pairs in the person’s genome.

Data Processing and Analysis:

Once the sequencing is complete, bioinformatics tools map back the reads (DNA fragments) to their original position in the genome based on a known reference sequence. This is called alignment as the purpose is to piece together the reads and rebuild the entire sequenced genome. Think of it as a tangram, where several shapes are arranged in a specific order to produce the desired picture. In this case however, it is being done with DNA fragments that are aligned to create the sequenced genome of the patient. From this step onwards, the assembled sequence is compared to a reference genome to identify any variants such as mutations, deletions, or even single nucleotide polymorphisms (SNPs), which in simple terms is a variation at a single position in a DNA sequence among individuals. Software is then used to predict the functional effects of each variant. For example, mutations in genes such as LDLR (linked to familial hypercholesterolemia) or SCN5A (linked to arrhythmias) can indicate a predisposition to heart disease.

What Happens Next if the Risk for CVD is Identified?

You may be wondering, now that the risk for a cardiovascular disease is identified in a person, what are the next steps that should be taken to address this? Well, in this case, Whole Genome Sequencing does not only provide a cure for CVDs but it also offers a guide for more proactive, targeted interventions with the aim of preventing disease progression and providing personalized care.

1. Pharmacogenomics and Personalized Medications

Not only does WGS reveal any genetic variants linked to cardiovascular diseases, but it also shows information about how an individual’s genes can affect their response to medications; this is known as pharmacogenomics. Based on these insights, doctors can prescribe medications that reduces the risk of adverse reactions and improves the efficacy of medications for managing heart-related concerns such as high blood pressure. As to the Food and Drug Administration, serious side effects from pharmaceutical medications affect 2 million people in the United States each year, potentially resulting in 100,000 deaths. These numbers are so large because either the medication was given in high dosage for a prolonged amount of time or because of unexpected outcomes of the drug due to genetic variation. With this said, WGS serves as the perfect first step to tackle CVDs before their symptoms even aggravate in a person.

2. Lifestyle Modifications

Although genetics play a role in inherited heart diseases, lifestyle changes can play a vital role in lowering the overall risk of cardiovascular symptoms from exacerbating. Aggressive lifestyle modifications such as diet and exercise would most likely be advised by the doctor. This includes shifting onto a Mediterranean diet, eating fiber rich fruits and vegetables to maintain healthy blood pressure levels, and avoiding foods high in sodium. In terms of physical fitness, cardiovascular exercises like running, walking, and strength training would be recommended to effectively manage CVD risks.

3. Family Screening

If a genetic predisposition to a cardiovascular disease is identified, family members may also have to undergo genetic testing or screening. Family screening can be highly advantageous for South Asian families since we know that CVDs are common among them. Furthermore, early detection is particularly important in conditions like familial hypercholesterolemia, which typically runs in families. Genetic screening of children and immediate-family members enables early detection and preventative interventions for them, allowing for a more targeted approach for care within families.

4. Gene Therapy (Emerging)

In the near future, technologies such as CRISPR becomes more advanced and are eventually used widespread, genes that are responsible for increasing the risk of CVDs in a person could be repaired, removed or even modified. Gene therapies could also be developed to correct mutations in genes like MYH7, which causes cardiomyopathy (primary disease of the heart muscle). By using these types of gene therapies, it could offer as a permanent solution for those with hereditary heart conditions.

Top Companies Working in the Field

1. Illumina

Illumina, founded by Jacob Thaysen, is a leader of innovating the future of precision medicine. The company has developed DNA sequencing technologies and they aim to accelerate the access of genomics as it has a strong potential to curing diseases and saving lives. Currently, Illumina is using Whole-genome sequencing to identify inherited disorders, more specifically in heart diseases. Their TruSight One Expanded Panels product give clinical research labs a cost-effective way to manage a wide range of tests and it includes 181 cardiac genes related to 18 inherited cardiac conditions.

2. Veritas

Veritas is another biotechnology company that is based on Whole Genome Sequencing. It is co-founded by George Church, who’s groundbreaking work has sparked multiple genetic discoveries, including the Human Genome Project, which was the first effort to map every gene in the human genome. Veritas provides genetic counselling to inform their patients which type of genetic testing would be suitable for them. The myGenome genetic test is one of their most common tests as it uses WGS and is designed for individuals who are are proactive in their health care. This procedure is heavily focused on cardiovascular diseases as well as cancer risk.

3. Verve Therapeutics

Verve Therapeutics has a full focus on targeting CVDs by leveraging their understanding of human genetics and gene editing. The company is co-founded by Sekar Kathiresan and he spent most of his career studying the inherited basis for heart attacks and developing solutions to improve the care of cardiovascular disease. Verve Therapeutics was established with a vision of creating gene editing therapies to address the root causes of CVDs.

Main Challenges Associated With Whole Genome Sequencing For Diagnosing CVDs

1. Data Interpretation and Insufficient Research

Since WGS is still a comparatively newer technology, there are challenges of it being able to translate the vast amount of data generated into actionable insights. Even though WGS can identify multiple genetic variants there a majority of variants of uncertain significance (VUS), meaning their impact on health is unclear. This complicates the development of precise treatment plans or interventions based on the findings of the WGS test. Keeping this in mind, genomic studies are disproportionately focused on European populations, which means that VUS would be more common for populations that are underrepresented in genomic databases such as South Asians. This highlights the need for more diverse genomic accuracy across different ethnicities.

2. Integrating into Healthcare

At one point, the WGS technique was prohibitively expensive — overtime its cost has plummeted and it is expected that it will become a part of mainstream healthcare. However, recent studies have suggested that in the near future, clinical applications of WGS may still be more costly and labour-intensive than anticipated. While sequencing itself is now affordable, the processes involved in analyzing the results make it expensive. Researchers at Stanford University School of Medicine, found that it costs about $17,000 per person to sequence the genome (woah) and study the average of about 100 genetic variations listed as important enough to be brought to the attention of each individual.

3. Ethical Concerns

With the vast amounts of personal health data that WGS generates, comes ethical and privacy concerns. This includes informed consent as the test is likely to reveal information not only about the patient but also their close relatives. WGS can also uncover genetic risks that are completely unrelated to the reason for testing. For example, if a person took a genetic test for a CVD risk, they may discover their predisposition to other illnesses as well. Addressing these factors are highly crucial to balance the benefits of WGS with preventing the misuse of genetic information.

Although there are quite a few barriers to overcome when implementing WGS in larger healthcare settings, this technology holds immense potential. It offers significant benefits, but there is still much work to be done in addressing challenges such as the ones listed above. By refining WGS and carefully considering such complications, we can transform it into a tool that offers far more advantages than drawbacks.

Conclusion and Future Directions

Utilizing Whole Genome Sequencing for diagnosing CVDs can be a gamechanger for the world’s population and specifically for high risk communities like South Asians. This technology can help us improve our well-being by taking proactive measures against this disease such as lifestyle modifications and personalized medicine. By shifting away from traditional approaches of how CVDs are being addressed, WGS could save millions of lives annually.

“Our intention in doing this analysis was to draw a line describing where we are with this technology at this point in time and identify how best to move forward… Things are becoming more clear, and the challenges to bringing this technique to the clinic are becoming crystallized. Whole-genome sequencing has the power to be absolutely transformative in the clinic.” — Euan Ashley, MD, associate professor of medicine and of genetics

I hope you all enjoyed this article and had a few key takeaways about how emerging technologies are revolutionizing medicine!

Hey! I am Deena Farrukh, a grade 10 student exploring genomics and how we can use it to tackle some of the world’s prevalent diseases. If you have any questions or would like to connect, feel free to contact me via email or LinkedIn:

• Email: farrukhdeena@gmail.com
• LinkedIn: https://www.linkedin.com/in/deena-farrukh-94701b337/

Citations

Conditions Treated. (n.d.). Stanford Health Care. https://stanfordhealthcare.org/medical-clinics/stanford-south-asian-translational-heart-initiative/conditions.html

Genomics Education Programme. (2023, April 14). Whole genome sequencing: From sample to report [Video]. YouTube. https://www.youtube.com/watch?v=rH6vsoyrc_U

Heggie, J. (2019, February 20). Genomics: a revolution in health care? Science. https://www.nationalgeographic.com/science/article/partner-content-genomics-health-care#:~:text=Early%20diagnosis%20of%20a%20disease,by%20alterations%20in%20our%20genes.

Why are South Asians dying of heart disease? Masala looks for answers. www.heart.org. (2023, May 17). https://www.heart.org/en/news/2023/05/17/why-are-south-asians-dying-of-heart-disease-masala-looks-for-answers

Li, C., Pan, Y., Zhang, R., Huang, Z., Li, D., Han, Y., Larkin, C., Rao, V., Sun, X., & Kelly, T. N. (2023). Genomic Innovation in Early Life Cardiovascular Disease Prevention and Treatment. Circulation Research, 132(12), 1628–1647. https://doi.org/10.1161/circresaha.123.321999

single nucleotide polymorphism / SNP | Learn Science at Scitable. (n.d.). https://www.nature.com/scitable/definition/snp-295/#:~:text=A%20single%20nucleotide%20polymorphism%2C%20or,C%2C%20G%2C%20and%20T.

Whole Genome Sequencing. (2022, October 30). Yale Medicine. https://www.yalemedicine.org/conditions/whole-genome-sequencing#:~:text=WGS%20translates%20all%20of%20the,or%20typos%2C%20in%20the%20genes.

Whole-genome sequencing for clinical use faces many challenges, study finds. (2014, March 11). News Center. https://med.stanford.edu/news/all-news/2014/03/whole-genome-sequencing-for-clinical-use-faces-many-challenges-study-finds.html