Personalised nutrition: Bridging ancient wisdom and modern science for cardiometabolic health

Understanding individual variability in dietary response

At a family gathering in rural Maharashtra, an elderly woman prepared a traditional meal for her three grandchildren. Despite eating the same dish, each individual had a different post-meal response: fatigue, discomfort, and elevated energy, respectively. While this might appear anecdotal, it underscores a foundational principle long recognised in Ayurveda. The body’s response to food is deeply individual.

Today, scientific inquiry supports this age-old view. Nutrigenomics and precision medicine reveal that genetic variability significantly affects how individuals metabolise nutrients and respond to dietary interventions. This convergence between genomics and Ayurveda forms the basis of a promising framework for chronic disease prevention.

Prakruti: Ancient typology meets molecular biology

In Ayurveda, Prakruti refers to an individual’s constitution, determined by the dominance of three doshas: Vata, Pitta, and Kapha. These profiles dictate physiological tendencies, stress responses, digestion, and disease predispositions. Importantly, no two individuals share an identical Prakruti, much like DNA fingerprints.

Emerging research provides compelling correlations. A 2015 study in Scientific Reports demonstrated gene expression profiles aligning with Prakruti types. Pitta types showed enhanced metabolic and inflammatory gene markers, while Kapha types had markers associated with lipid metabolism and fat storage. Similarly, a 2022 article in Frontiers in Pharmacology highlighted how Ayurgenomics, which combines genetic testing with Prakruti analysis, may outperform conventional tools like BMI in assessing health risks.

Clinical relevance: Cardiometabolic disorders and constitutional typing

India’s rising burden of non-communicable diseases, particularly Type 2 diabetes and cardiovascular disorders, demands more individualised preventive strategies. Traditional interventions typically adopt a one-size-fits-all approach that often ignores biological diversity.

By incorporating Prakruti profiling alongside genomic data, clinicians can stratify patients more effectively. For example:

• Vata-dominant individuals may present with erratic glycemic patterns and stress-induced cardiac symptoms. These cases may benefit from calming and stabilising interventions.

• Pitta types tend toward inflammatory profiles which may manifest as hypertension or atherogenesis. These individuals could respond better to anti-inflammatory and cooling dietary strategies.

• Kapha types, with a predisposition to obesity and lipid disorders, often require metabolic stimulation and calorie-conscious regimens.

These insights can be integrated into cardiac rehabilitation, endocrinology consults, and even primary care screening protocols.

Towards personalised preventive protocols

In clinical settings, combining conventional diagnostic tools such as 2D Echo, HRV analysis, or glucose monitoring with constitutional assessments could refine treatment pathways. The aim is not to replace evidence-based medicine but to complement it with individualised parameters that consider the patient’s biological tendencies.

Customised lifestyle interventions such as dietary modulation, structured exercise, and targeted herbal or pharmaceutical support can be deployed with greater efficacy when mapped to both Prakruti and genetic markers. This alignment allows for risk attenuation at an earlier stage and may reduce dependence on pharmacotherapy in chronic disease management.

Institutional integration: Framework, not brand

From a healthcare administration perspective, implementing such integrative models requires a systemic framework rather than brand-specific solutions. Training clinicians in Ayurgenomics, establishing interdisciplinary panels, and standardising Prakruti assessments within electronic medical records could operationalise this model at scale.

Several institutions are piloting this integrative approach with encouraging preliminary outcomes. These include reduced medication load, improved quality of life indices, and enhanced patient adherence to lifestyle changes. However, rigorous longitudinal studies and protocol standardisation remain critical to wider adoption.

Conclusion: A systems-level perspective on personalised care

Ayurveda’s Prakruti framework, validated by modern genetic research, offers a lens through which personalised nutrition and preventive care can be approached more systematically. As hospital systems face the dual challenge of rising non-communicable diseases and constrained resources, strategies that combine traditional models with data-driven insights are not merely complementary. They may be essential.

Rather than asking patients to conform to a rigid diet plan, clinicians can leverage constitution-based assessments to craft dietary and lifestyle guidance that aligns with both ancient principles and contemporary science.

This shift from population-based treatment to precision prevention has the potential to reshape how cardiometabolic diseases are managed in India and globally.