India’s first diabetes biobank set to revolutionise care, unlock genetic keys, says Dr Sonali Kagne
By Arunima Rajan
In an interview with Arunima Rajan, Dr Sonali Kagne, endocrinologist at Sir H. N. Reliance Foundation Hospital and Research Centre talks about the significance of India’s first diabetes biobank, its functionality and its impact on diabetes research and treatment in India.
Can you explain the significance of India’s first diabetes biobank set up by ICMR and MDRF? Why is this such a landmark initiative for diabetes research in India?
The biobank, established by the Indian Council of Medical Research (ICMR) and Madras Diabetes Research Foundation (MDRF) is a groundbreaking initiative for diabetes research in India. It provides a centralised repository of high-quality biospecimens, such as blood, urine, and DNA, linked with detailed clinical data. This resource is vital for understanding the genetic, environmental, and lifestyle factors driving diabetes in the Indian population. It enables large-scale, high-impact research to identify new biomarkers, risk factors, and therapeutic targets tailored to India’s unique diabetes burden.
How does the biobank function? Can you walk us through the process of collecting, processing, and storing biospecimens for research?
The biobank collects biospecimens from diverse individuals, including those with Type 1, Type 2,and gestational diabetes, as well as healthy controls. The process involves:
Collection: Blood, urine, and DNA samples are collected under strict ethical guidelines and
informed consent.
Processing: Samples are processed to extract serum, plasma, and genetic material, ensuring high quality.
Storage: Advanced cryopreservation techniques are used to store samples at ultra-low
temperatures, preserving them for future research.
Data Integration: Each sample is linked with clinical, demographic, and lifestyle data,
creating a rich database for researchers.
The biobank includes blood samples for various types of diabetes—Type 1, Type 2 in the young, and gestational diabetes. Why is it important to focus on these specific types, especially in the Indian population?
These forms of diabetes are of particular relevance in India:
Type 1 Diabetes: Often affecting children and young adults, it requires lifelong insulin therapy. Studying this group can unravel genetic and autoimmune factors.
Type 2 Diabetes in the Young: Rising prevalence in young Indians poses unique challenges, including rapid disease progression and complications.
Gestational Diabetes (GDM): GDM increases risks for both mother and child, including a higher likelihood of developing Type 2 diabetes later in life.
Studying these types in the Indian context helps address the genetic predisposition, early onset, and pregnancy-related diabetes risks prevalent in the population.
It is noted that Indians with diabetes often exhibit unique clinical features. Can you elaborate on these features and why they matter for developing better treatment strategies?
Indians with diabetes often exhibit:
High visceral fat and insulin resistance despite having a lower body mass index (BMI).
Early onset of Type 2 diabetes, sometimes in their 20s or 30s.
Higher risk of complications, such as cardiovascular disease and kidney failure, even with modest elevations in blood sugar levels. These features underscore the need for region-specific screening, treatment strategies, and guidelines to address the unique pathophysiology and progression of diabetes in Indians.
How will the biobank aid in identifying novel biomarkers for early diagnosis and help pave the way for personalized diabetes care?
The biobank enables researchers to:
Discover biomarkers for early detection of diabetes and its complications, such as kidney disease or neuropathy.
Identify genetic and molecular factors unique to the Indian population.
Develop personalised treatment plans by understanding patient-specific responses to drugs and interventions. This can lead to early intervention, better disease management, and improved patient outcomes.
One-fourth of the global diabetes burden is in India. From your perspective, what are the key factors driving this surge in both urban and rural areas?
The surge is fueled by:
Urbanization: Sedentary lifestyles, unhealthy diets, and stress.
Rural Changes: Transition from traditional diets to processed foods and reduced physical activity.
Genetic Predisposition: Indians are more prone to insulin resistance and abdominal obesity.
Gestational Diabetes: Increasing rates among pregnant women, leading to intergenerational transmission of risk.
These factors emphasize the importance of early detection, prevention, and lifestyle interventions.
The ICMR study, which surveyed over 1.2 lakh people across India, highlights the increasing prevalence of diabetes. What trends from this data do you find particularly concerning?
The survey highlighted:
Rising prevalence in both urban and rural areas.
Undiagnosed cases: Many individuals are unaware of their condition, leading to late diagnosis and complications.
Pre-diabetes burden: High rates of individuals with borderline blood sugar levels suggest an impending diabetes epidemic.
This data calls for widespread awareness campaigns and proactive screening programs.
Longitudinal studies supported by the biobank could provide critical insights into diabetes progression. How do such studies improve prevention, diagnosis, and management strategies for patients?
Longitudinal studies track individuals over time to observe disease progression. They:
Identify early risk factors and predictors of complications.
Help evaluate the long-term effectiveness of treatments and lifestyle changes.
Provide evidence to design prevention strategies and optimize clinical guidelines.
Such studies are crucial for understanding how diabetes evolves in the Indian population.
What role do you see technology, like AI or machine learning, playing in analyzing the data gathered by biobanks to enhance diabetes care?
AI and machine learning can: • Analyze vast biobank data to detect patterns and correlations.
Predict individual risk levels and disease trajectories.
Identify new therapeutic targets and tailor personalized treatments.
These technologies accelerate research, making it more precise and impactful.
What are the key challenges in translating the biobank’s research outcomes into practical solutions for diabetes care, especially in regions with limited healthcare infrastructure?
Key challenges include:
Healthcare Inequity: Limited access to advanced diagnostics and treatments in rural and underserved regions.
Awareness Gaps: Lack of awareness among patients and healthcare providers about novel findings.
Cost Constraints: Ensuring affordability of innovative therapies derived from research.
Addressing these challenges requires collaboration between researchers, policymakers, and healthcare providers to make scientific advances accessible to all.