close_game
close_game

Fight against heart disease needs precision medicine

ByNaresh Trehan
Sep 27, 2024 09:14 PM IST

The impact of early-onset CVD extends beyond health, causing an estimated annual productivity loss of ₹11.8 lakh crore. Preventing CVDs is not just a health imperative but an economic necessity.

September 29 is observed as World Heart Day. In India, a heart attack occurs every 33 seconds, claiming over two million lives annually. Yet, up to 80% of these deaths are preventable. Almost tripling in prevalence since the 1990s, cardiovascular diseases (CVDs) have silently become India’s leading killer, claiming one in every four lives. The average age for a first heart attack in India is just 50, a decade earlier than in western countries. Shockingly, CVDs also account for 45% of deaths in the 40–69-year age group. This silent epidemic pushes families into financial distress and diminishes survivors’ quality of life.

Standard CVD prevention strategies fail to address the country’s genetic diversity and cultural nuances (SewcreamStudio - stock.adobe.com)
Standard CVD prevention strategies fail to address the country’s genetic diversity and cultural nuances (SewcreamStudio - stock.adobe.com)

The impact of early-onset CVD extends beyond health, causing an estimated annual productivity loss of 11.8 lakh crore. Preventing CVDs is not just a health imperative but an economic necessity.

However, current prevention strategies face significant challenges. Traditional health care paints all 1.4 billion Indians with the same broad brush, leading to imprecise risk assessments and patient non-compliance. Also, the common refrain of “What harm can one samosa do?” echoes the sentiments of many. This emotion gains credence as millions with seemingly unhealthy habits live long lives, while some seemingly healthy individuals succumb to sudden heart attacks. The solution lies not only in regular and earlier check-ups but also in leveraging predictive precision medicine and Artificial Intelligence (AI).

Standard CVD prevention strategies fail to address the country’s genetic diversity and cultural nuances. Risk prediction models, largely based on western populations, inadequately capture India’s unique risk profile. Tobacco use, physical inactivity, genetic predisposition, poor diet, and air pollution further compound the problem.

Traditional cardiac risk assessment tools only help gauge a broad probability of developing heart disease. They essentially only answer if you are at high risk or low risk. While this categorisation is critical, it does not identify exact causal factors or account for short-term risk for scientific follow-up, leading to a majority of patients getting over-treated or under-treated.

Patient compliance is also a major challenge, stemming from resistance to testing, over-reliance on unproven lifestyle modifications, and the tendency to “carry on” until symptoms become unbearable. Cultural beliefs further complicate matters. The perception of traditional Indian diets as inherently healthy overlooks their high carbohydrate content, while the normalisation of conditions like hypertension and diabetes as “common” or “familial” leads to a dangerous lack of urgency in seeking medical attention. These challenges underscore the need for a more nuanced, personalised approach to CVD prevention.

Let’s consider the case of Amit, a 38-year-old IT professional from New Delhi. Amit, health-conscious and proactive, undergoes his first comprehensive health check-up. His initial tests are within normal range, albeit with slightly elevated LDL cholesterol. Following standard protocols, his doctor advises statins, exercise and healthy eating with regular follow-up.

Amit is resistant to taking medication at his age but understands his risk given his father’s angioplasty at 52. He opts for additional assessments using predictive precision medicine that combine genetic and clinical data with lifestyle factors using AI to create a comprehensive personalised risk profile.

The tests offered a more accurate understanding of Amit’s CVD risk: Advanced lipid panel confirms high lipoprotein(a), a risk factor often missed in standard tests; genetic testing detects variation in the APOC3 gene, associated with regulation of triglyceride levels; coronary artery calcium (CAC) scoring shows deposits in the arteries, a marker of plaque buildup; AI-driven risk assessment predicts very high 10-year CVD risk — much higher than suggested by traditional calculators. These insights allow Amit’s doctor to create a more personalised 10-year CVD prevention plan; immediately starting Amit on statins, more aggressive lifestyle modification, regular lipid profile and other relevant investigations.

This risk assessment also made Amit more attentive to health advice. By 55, despite a family history of early heart disease, Amit maintained good cardiovascular health.

While standard testing remains crucial for baseline health assessment, precision medicine offers deeper insights into individual risk factors, allowing for more accurate risk stratification and tailored prevention strategies. Mass implementation of predictive precision medicine may not be immediately feasible due to cost and limited availability. But incorporating advanced genetic testing and biomarker analysis into corporate health check-ups offers a starting point. This approach not only protects a vital segment of our workforce but also provides a resource-effective model that could unlock cost-effectiveness when implemented at scale.

This data could significantly advance how we approach cardiovascular health at the population level. By analysing this comprehensive dataset, researchers could identify novel biomarkers and risk factors unique to the Indian context. This information could be used to develop new prediction models, algorithms, or tools more accurately tailored for our population. Such tools, when validated and implemented, could enhance the effectiveness of existing government programmes targeted to address the rising incidence of non-communicable diseases. This could improve risk stratification at primary health centres, potentially leading to more targeted interventions and efficient use of tertiary care resources for high-risk individuals.

As we advance, ethical challenges around data privacy, informed consent, and genetic discrimination are likely to emerge necessitating the formation of comprehensive guidelines for the use of genetic and biomarker data. Despite the potential challenges, the integration of predictive precision medicine into India’s CVD management strategy offers an unprecedented opportunity to tackle this epidemic holistically.

Dr Naresh Trehan is chairman and managing director of Medanta.The views expressed are personal

Get Current Updates on...
See more
SHARE THIS ARTICLE ON
Share this article
SHARE
Story Saved
Live Score
OPEN APP
Saved Articles
Following
My Reads
Sign out
New Delhi 0C
Thursday, October 10, 2024
Start 14 Days Free Trial Subscribe Now
Follow Us On