A new BHARAT- establishing baseline health parameters for the Indian population

The Hindu

2 days ago

We don't all age the same way, but we all do age. We intuitively recognise frailty when things start to slow down. Ageing unfolds at different rates, over time, between individuals, within and across populations. Often, it happens in bursts.
Ageing is complicated. It is driven by molecular and cellular interactions and is shaped by one's environment, lifestyle, and socioeconomic conditions. This means one's chronological age often doesn't reflect how old one's body really is.
Since researchers discovered in 1935 that ageing can be altered, they have been looking for reliable biological clues, called biomarkers, that in isolation or together can indicate how old our bodies are and how they might respond to factors such as diet, exercise, etc.
Biomarkers of ageing
Last year, the Indian Institute of Science (IISc), Bengaluru, launched a large-scale study called BHARAT, short for 'Biomarkers of Healthy Aging, Resilience, Adversity, and Transitions', as part of its Longevity India Program. The study aims to map the physiological, molecular, and environmental indicators that drive ageing in the Indian population.
'We lack clear information on what features define or influence healthy ageing,' says Deepak Kumar Saini, convener of BHARAT and professor of development biology and genetics at IISc. 'We are building an information portal to understand the rules of healthy ageing in Indians.'
Worldwide, life expectancy has risen significantly over the past few decades. In India it climbed 4.1 years to 67.3 in the first two decades of this century.
Living longer doesn't mean living healthier, however. Studies have predicted a 168% increase in Parkinson's disease cases in India by 2050 and a 200% rise in dementia across low- and middle-income countries. Yet much of what we know about health and disease risk comes from studies in Western populations, which means the diagnostic tools, biomarkers, and even treatments may not be optimal for people in India or other non-Western countries.
Gaps for patients in Global South
This limited focus has created a gap between population-based biomarkers and diagnostic cut-offs for people in the Global South. This can lead to misdiagnosis and treatments that don't reflect how diseases progress or respond to therapeutics in different groups.
'Western values for cholesterol, vitamin D, or B12 may label many Indians as deficient. But are these truly abnormal within our context? Our study aims to answer that. We are not only identifying biomarkers for healthy ageing but also building the Bharat Baseline — a reliable reference for what is normal in the Indian population,' Prof. Saini says.
Earlier this year, researchers from Sichuan, China, reported in Scientific Reports that certain biomarkers for breast cancer, such as high levels of high-density lipoprotein cholesterol, could signal an elevated risk in European populations but may serve as supportive indicators in Asians.
'We see differences in inflammatory markers. For instance, C-reactive protein (CRP) levels tend to be elevated in Indians even without acute illness. This inflammation often results from early-life infections, environmental toxins, or chronic nutritional and metabolic issues,' Shawn T. Joseph, senior consultant, head and neck surgical oncology, VPS Lakeshore Hospital in Kochi, says. 'Applying Western CRP cut-offs risks missing early warning signs of cardiovascular or metabolic disease in Indian patients,' he adds.
An India-specific database
BHARAT's goal is to change this. Its database will include genomic biomarkers (like mutations linked to disease susceptibility), proteomic and metabolic indicators (reflecting biological pathways and metabolic health), and environmental and lifestyle factors.
Identifying early warning signs of age-related changes can enable better prediction, intervention, and potentially delay the onset of disease. There is a need for proactive markers of health, indicators that can tell when an organ is functioning below its optimal level, even if it is not yet diseased. For instance, your liver age is more than your chronological age. To do that, researchers must sift through large, many-dimensional datasets and plan to take the help of artificial intelligence (AI) models.
'AI and machine learning are essential to integrate and analyse layered data to see the full picture. It can simulate the impact of interventions and augment existing datasets to improve signal detection that may otherwise be missed in high-dimensional, small-sample studies. This will help us choose the most effective interventions before launching costly trials,' says Tavpritesh Sethi, professor of computational biology at the Indraprastha Institute of Information Technology, Delhi, who is also one of the investigators of BHARAT.
However, if the AI models' training datasets don't reflect local realities, they risk perpetuating health inequities. India's population is genetically, environmentally, and socioeconomically diverse. Capturing this diversity in a single database is crucial but also logistically complex. Prof Saini anticipates a few challenges, including the difficulty of obtaining samples from healthy adults, securing long-term government and philanthropic funding, and expanding the study to collect samples from across the country.
(Rupsy Khurana is science communication and outreach lead at the National Centre for Biological Sciences, Bengaluru. [e-mail])