ICMR-MDRF Diabetes Biosamples: Cohort profile

Biobank at Madras Diabetes Research Foundation (MDRF)

Biobanks are critical in biomedical research, collecting, processing, storing, and distributing biospecimens to support scientific research. There is no universally agreed common terminology for biobank and several terminologies exist, such as biorepository, bio-library, biospecimen resource, etc. However, all of them broadly refer to a ‘large-scale collection of human biological materials’. The ICMR guidelines define biobanks as organized collections of human biological materials with associated data for research and potential commercial purposes. MDRF, a non-profit organization recognized by various Indian research organizations [ICMR Center for Advanced Research on Diabetes, ICMR - Collaboratiing Centre of Excellence (ICMR-CCoE) the Department of Scientific and Industrial Research (DSIR) of the Ministry of Science and Technology, Government of India as a Scientific and Industrial Research Organization (SIRO) (since Nov. 1996)], houses a biobank at its Siruseri facility (29 km from the heart of Chennai city, Tamil Nadu). The 3,700-square-foot facility includes liquid nitrogen containers (–196°C) and freezers (–20°C or –80°C), with over 800,000 samples stored. The key operations of the MDRF biobank include (i) collection and processing of samples, (ii) barcoding the sample and linking to the participant information, (iii) sample storage and inventory system in the appropriate vials and boxes, and (iv) retrieval of the samples as and when required.

Samples available at the MDRF Biobank

This article focuses on two ICMR-funded projects:

(i) ICMR–India Diabetes (ICMR–INDIAB) study: It is one of the large epidemiological studies on diabetes with a sample size of 1,20,000 nationally representative individuals, covering every State of India. This cross-sectional, community-based study was done in adults of either sex, aged 20 yr in phases from 2008 to 2020 and sampled 33,537 urban and 79,506 rural residents (total, n=113,043) in 31 States/ Union Territories (UT) of the country⁷. In Phase I, four States viz Tamil Nadu (south), Chandigarh (north), Jharkhand (east), and Maharashtra (west) were studied from 2008 to 2010. The remaining States were surveyed as follows: Phase II: Andhra Pradesh, Telangana, Bihar, Gujarat, Karnataka and Punjab (2012–2013), Phase III: Delhi, Madhya Pradesh, Rajasthan and Uttar Pradesh (2017–2018), Phase IV: Kerala, Goa, Puducherry, Haryana and Chhattisgarh (2018–2019), North East Phase: Assam, Arunachal Pradesh, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura (2011–2017) and Phase V: Himachal Pradesh, Uttarakhand, Odisha and West Bengal (2019–2020). The surveys of Andaman and Nicobar, Dadra and Nagar Haveli and Daman and Diu, Lakshadweep and Kashmir, Jammu and Ladakh were completed recently in 2024⁷.

Each State, National Capital Territory, or Union Territory was divided into urban (towns, including metropolitan areas, where applicable) and rural (villages) components. A stratified multistage sampling approach was employed. Villages served as the primary sampling units for rural areas, while census enumeration blocks were used for urban areas. Households were then selected systematically, 24 from urban and 56 from rural areas. A door-to-door assessment was conducted, and from each selected household, one individual was chosen at random using the World Health Organization (WHO) Kish method, ensuring unbiased selection across sex and age categories⁶. In every fifth individual and those with diabetes (both self-reported and newly diagnosed diabetes), fasting samples were drawn, and the aliquots from these samples have been stored for future use.

(ii) Registry of people with diabetes in India at a young age at the onset: Registries are crucial for understanding disease conditions, including demographic, socioeconomic, clinical, and biochemical profiles, complications, and treatment modalities. In 2006, ICMR launched the country’s first national multi-centre clinic-based registry on youth-onset diabetes. The initiative aimed to investigate disease patterns and variations across different regions of India¹⁰. The ICMR–YDR comprises 11 Regional Collaborating Centers (RCCs) selected for their expertise in clinical trials and diabetes research. RCCs recruit patients and oversee data collection from Reporting Centers (RCs), ranging from individual physician clinics to comprehensive hospitals^10,11.

The ethics committee approvals were obtained from all Regional Collaborating Centres. An ethical approval letter was obtained from the Institutional Ethics Committee of Madras Diabetes Research Foundation for the YDR at the onset, for all the three phases of the study. Phase I of the registry used baseline and follow-up proformas to collect data on demographics, clinical history, family history, biochemical details, treatment, and complications. In Phase II, blood samples were collected for serum and genetic analysis where the facilities allowed. Phase III (2020–2025) includes registry, cohort, and surveillance components, managed by the Technical Coordinating Unit at the All India Institute of Medical Sciences (AIIMS), New Delhi. Detailed methods have been published elsewhere¹⁰, including annual follow-up data managed electronically. Phase I baseline data, and Chennai’s RCC03 results have been published^11,12. Phase II’s biobank at Dr. Mohan’s Diabetes Specialities Centre (DMDSC) stores 709 serum samples from type 1 diabetes (T1D) and type 2 diabetes (T2D). Phase III’s ongoing cohort biobank aims to recruit multiple aliquots of biospecimens from 750 individuals with T1D and T2D from four centres in Chennai, South India.

Key operations of the biobank at MDRF

Frequency of participant follow up

Assessment of baseline clinical and biochemical measures

Registry of people with diabetes in India with young age at onset

Phase II: Clinical and biochemical details were collected, and routine tests were done. Available study variables under the young diabetes registry are given in Table IV. Table V provides the clinical and biochemical characteristics of individuals with T1D and T2D.

Phase III: Blood and urine samples were collected at baseline and follow-up visits and stored at -80°C. Tests include fasting plasma glucose, HbA1c, lipid profile, serum creatinine, microalbuminuria, C-peptide (fasting), C-reactive protein, Glutamic acid decarboxylase (GAD), anti-thyroid peroxidase (anti-TPO) antibodies, retinal examination, bio-thesiometry, and foot examination. The biospecimens being collected for the cohort are given in Supplementary Table I. Supplementary Table II provides the total number of serum, plasma, and genetic samples collected during Phase II from DMDSC and Phase III samples proposed for future storage (Baseline, 1^st Follow-up, and 2^nd Follow-up).

Quality assurance and quality control strategies

Statistical analysis

All statistical analyses were conducted using SPSS software version 24.0 (SPSS Inc., Chicago). An independent t-test was used for continuous variables and the chi-square test for categorical variables to compare baseline clinical and biochemical characteristics. In Table II, the continuous variables were expressed as mean ± standard error (SE), and categorical variables as percentages with 95 per cent confidence interval (CI). In Table V, continuous variables were expressed as mean ± standard deviation (SD). A P-value of <0.05 was considered statistically significant.

ICMR-INDIAB study

This large, nationally representative study reported that the prevalence of diabetes and metabolic NCDs in India was greater than the earlier estimates, with 101 million individuals diagnosed with diabetes and 136 million with prediabetes⁷. Hypertension, generalized, and abdominal obesity affected 315 million, 254 million, and 351 million people, respectively. Additionally, 213 million had hypercholesterolemia, and 185 million had high LDL cholesterol. The study also indicated that the diabetes epidemic was stabilizing in more socio economically advanced States but rising in less developed States¹³.

The prevalence of undiagnosed hypertension was high, with salt intake ≥6.5 g per day increasing hypertension risk. Factors associated with hypertension included age, male sex, urban residence, obesity, diabetes, physical inactivity, and alcohol consumption¹⁴. High rates of obesity were found, with independent risk factors including female sex, hypertension, diabetes, higher socioeconomic status, physical inactivity, and urban residence¹⁵. Dyslipidemia was also highly prevalent, with over 80 per cent of individuals aged 35–64 yr exhibiting lipid abnormalities, and high rates even among those aged 20–24 yr¹⁶.

The study found that less than 10 per cent of Indians engaged in recreational physical activity, highlighting the need to promote physical activity¹⁷. Only 43.2 per cent of the population had heard of diabetes, emphasizing the need for large-scale diabetes awareness and education programme¹⁸. Rural-to-urban migration was associated with an increased risk of diabetes and cardiometabolic abnormalities¹⁹. The MDRF-Indian Diabetes Risk Score (IDRS) was effective for diabetes screening in Asian Indians²⁰. Age-specific HbA1c cut-offs were suggested to prevent overdiagnosis and unwarranted treatment in the elderly²¹.

This study also recorded the achievement of diabetes treatment targets in India. It found that about a third of the population with diabetes had good glycaemic control, and fewer than half had good blood pressure control and good LDL cholesterol control²². In the past year, the majority of individuals with diabetes had not assessed their HbA1c level²³. These findings can help governments improve diabetes care delivery and surveillance. The study also derived macronutrient recommendations for diabetes remission and prevention in Asian Indians, suggesting reduced carbohydrates and increased protein intake²⁴.

Registry of people with diabetes in India with young age at onset

Major biobanks available globally

Of the various biobanks available globally, the most well-known is the UK Biobank, supported by the National Health Service (NHS), which is a vast biomedical database with genetic, lifestyle, and health information from 500,000 UK participants. The collected information comprises phenotypic, genomic, and imaging data derived from direct assessments, verbal interviews, online questionnaires, and electronic health records. This dataset continues to expand as new biomedical data are added through ongoing assessments and longitudinal follow up. The UK biobank’s key features include easy accessibility, a large-scale prospective approach, extensive and varied risk factor data, and thorough linkage to health outcomes. These features allow researchers from academia and industry worldwide to make scientific discoveries³⁰. The findings from the UK biobank are invaluable, but its significance extends beyond immediate clinical relevance, as it provides valuable insights for researchers setting up population-cohort and genomic-medicine projects in other regions. The UK biobank has about 3,229 publications so far, which keeps growing^31-33. Some other prominent biobanks in the world and the number of publications from each of these are as follows: JDRF Network for Pancreatic Organ Donors with Diabetes (nPOD)³⁴, United States (n=354), Mayo Clinic Biobank³⁵, United States (resource for 280 studies), Australasian Biospecimen Network, Australia (n=11), BancoADN, Spain (n=100), National Institute of Diabetes and Digestive Kidney diseases, United States (n=2,358), China Kadoorie Biobank^36,37, China (n=1,658), FINNGEN Biobank³⁸, Finland(n=1,629), the Danish Centre for Strategic Research in Type 2 Diabetes³⁹, Denmark, Australian Prostate Cancer Bio-Resource, Australia, Canadian Tumor Repository Network⁴⁰, Canada, Shanghai Outdo Biobank, China and BioMe Biobank, United States.

Available biobanks in India

Many biobanks exist in India, each focusing on a particular area of biomedical and health research. These biobanks make major contributions to a range of research domains, such as cancer, genetics and liver diseases. Some examples include, the National Cancer Tissue Biobank (NCTB)⁴¹, Chennai, TamilNadu, National Liver Disease Biobank (NLDB)⁴², New Delhi, Rajiv Gandhi Cancer Institute and Research Centre (RGCIRC)⁴³, New Delhi, National Institute of Mental Health and Neurosciences (NIMHANS)⁴⁴, Bangalore, Karnataka, the Tata Medical Centre Biorepository (TiMBR)⁴⁵ Kolkata, West Bengal, Sapien BioSciences⁴⁶, Hyderabad, Telangana, National Centre for Cell Sciences (NCCS)⁴⁷, Pune, Maharashtra and Accelerator Programme for Discovery in Brain Disorders using stem cells (ADBS)⁴⁸, Bangalore, Karnataka. However, diabetes-specific biobanks are limited²⁹. Given India’s high prevalence of diabetes, there is a pressing need for a diabetes biobank. Such a biobank would be an invaluable resource for researchers and healthcare professionals, providing a comprehensive repository of biological samples and related health data. This would facilitate in-depth studies on the genetic, environmental, and lifestyle factors contributing to diabetes in the Indian population. Over 150,000 samples are stored in the MDRF biobank. Combining the data sources with the biobank can enhance the knowledge base and sample utility. Only with the establishment of long-standing, well-characterized biobanks combined with a continuous stream of innovative ideas and strategies, will the health care costs be reduced²⁹.

Biobanks are vital for advancing biomedical research, offering invaluable biological materials that support personalized medicine through omics technologies. They maintain high standards in sample collection, processing, and storage, ensuring sample quality and research reproducibility. Centralized sample collection is efficient, reducing duplication of effort, and enabling longitudinal studies over extended periods. However, biobanks face challenges including high costs for infrastructure, equipment, and ongoing operations, limiting accessibility and financial sustainability. Ethical complexities around informed consent and privacy must be carefully managed, along with operational hurdles in personnel, equipment, and sample transportation. Addressing these challenges with improved technology, funding, and ethical oversight can enhance biobanks’ impact on health research.

The MDRF biobank serves as a repository for biological samples from various research projects, equipped with high-quality practices including monitored freezers, IT infrastructure for sample tracking and management, and ample space for future expansion. It adheres to the ICMR guidelines⁴⁹ and supports diabetes research, providing insights into disease mechanisms and facilitating long-term studies. Investment in biobanks is crucial for health research infrastructure, enabling scientifically sound decisions and potential treatments. Future plans include automating biobank operations with technologies like AI and robotics to optimize sample handling and analysis.

Data access statement

Data from the ICMR-INDIAB and the YDR will be available on reasonable request to the corresponding author, Dr.Viswanathan Mohan (email: drmohans@diabetes.ind.in), and lead investigator, Dr.Ranjit Mohan Anjana (email: dranjana@drmohans.com).