Biomarkers

Chemical Biomarkers will help transform early disease diagnosis and precision healthcare. Read here to learn more.

Chemical biomarkers are gaining prominence as tools for detecting disease-associated molecular changes, monitoring disease progression and supporting personalised treatment. Advances in blood-based biomarkers for neurological conditions such as Alzheimer’s disease are creating opportunities for less invasive diagnosis and reducing dependence on expensive or invasive investigations.

In May 2025, the US Food and Drug Administration cleared its first blood test to aid in diagnosing Alzheimer’s disease in adults aged 55 and above who have signs and symptoms of the condition. The development illustrates the growing clinical potential of blood-based biomarker testing, although such tests must be interpreted alongside clinical assessment.

In India, initiatives such as the GenomeIndia Project and the BHARAT Study are strengthening the foundations for population-specific biomedical research and precision healthcare.

What Are Chemical Signatures or Biomarkers?

A biomarker is an objectively measurable characteristic that indicates a biological process, a disease-related condition or a response to treatment. Biomarkers may include proteins, metabolites, nucleic acids, hormones, antibodies, genetic variants or patterns of multiple molecules.

Chemical signatures refer more specifically to measurable molecular patterns that provide information about biological conditions.

How do biomarkers work?

• Molecular changes: Disease processes may alter the production, concentration, structure or activity of particular molecules.
• Sample collection: Biomarkers may be measured in blood, urine, saliva, cerebrospinal fluid, tissue or other biological samples.
• Analytical detection: Laboratory techniques identify and quantify these molecular changes.
• Clinical interpretation: Results are interpreted alongside symptoms, medical history, examination findings and other diagnostic evidence.

Technologies used for biomarker detection

• Mass spectrometry: Identifies and quantifies molecules based on their mass-to-charge ratios.
• Chromatography: Separates the components of complex mixtures before identification or quantification.
• Immunoassays: Use antibodies to detect specific proteins or other target molecules.
• Molecular diagnostics: Detect genetic material, mutations and other nucleic-acid markers.
• Biosensors: Convert a biological recognition event into a measurable signal, potentially enabling rapid and portable testing.

The choice of technology depends on the biomarker, the required sensitivity, sample type, testing environment and cost.

Significance of Biomarkers in Healthcare

1. Early and more accurate diagnosis

• Biomarkers can identify disease-associated changes before symptoms become pronounced or when clinical signs overlap across conditions. This can support earlier diagnostic evaluation and timely intervention.
• However, not every biomarker becomes abnormal before symptoms, and a positive result does not always establish that a person has a particular disease.

2. Less-invasive testing

• Blood-based tests can reduce reliance on procedures such as lumbar puncture and certain imaging investigations.
• For example, validated blood tests measuring Alzheimer’s-associated proteins may help clinicians determine which patients need further investigation.

3. Precision medicine

• Biomarkers can help identify disease subtypes, estimate risk, inform treatment selection and identify patients who may benefit from particular therapies.
• This supports a shift from a uniform treatment approach towards more individualised healthcare.

4. Monitoring disease progression and treatment response

• Repeated measurements can help clinicians assess changes in disease activity or treatment response.
• The usefulness of serial testing depends on whether changes in the biomarker reliably reflect meaningful changes in the patient’s condition.

5. Preventive healthcare and public health research

• Biomarkers can improve understanding of risk factors, ageing, environmental exposures and disease patterns.
• Population-level research may help identify groups requiring closer monitoring and inform preventive interventions.

Important Biomarkers and Associated Diseases

Note: Biomarkers differ in their level of clinical validation. A marker may be useful for research or risk assessment without being sufficiently reliable for routine diagnosis on its own.

India’s Initiatives in Biomarker and Genomic Research

1. GenomeIndia Project

Launched in January 2020 and funded by the Department of Biotechnology, the GenomeIndia Project aims to map genetic diversity across India’s population.

• Whole-genome sequencing has been completed for more than 10,000 individuals representing diverse population groups.
• The project supports research into genetic variation, disease susceptibility, inherited disorders and differences in drug response.
• The genomic dataset provides a resource for developing diagnostic tools and advancing precision medicine suited to India’s population.

Significance: India’s considerable genetic diversity means that findings based primarily on other populations may not always translate directly to Indian patients. Population-relevant genomic evidence can help improve the interpretation of genetic risk and the development of appropriate diagnostics.

2. BHARAT Study

• The BHARAT Study, Biomarkers of Healthy Aging, Resilience, Adversity, and Transitions, is a pan-India research initiative led by the Indian Institute of Science under its Longevity India Programme.
• It uses comprehensive clinical assessments, lifestyle and environmental information, and multi-omics and multimodal analyses to investigate ageing patterns in the Indian population.
• Its objective is to identify markers associated with ageing-related conditions and support interventions that improve healthspan.

Significance: Chronological age does not fully capture biological ageing. Understanding how genetics, nutrition, environment and socioeconomic circumstances influence ageing can support more population-relevant health assessments.

3. Indian Biological Data Centre

• The Indian Biological Data Centre provides infrastructure for archiving and accessing biological datasets, including GenomeIndia data under applicable access and governance frameworks.
• Such infrastructure can facilitate collaborative research, reproducibility and the development of indigenous diagnostics, provided data are handled responsibly and securely.

Major International Genomics and Biomedical Research Initiatives

These initiatives differ in their design and scope: some primarily investigate genetic variation, while others integrate genomics with clinical and environmental information.

Genomic data can contribute to biomarker discovery, but a genetic variant is not automatically a validated biomarker for diagnosing an active disease.

Challenges in Biomarker-Based Diagnosis

1. Accuracy and specificity

• A biomarker may be associated with several diseases or physiological processes. For example, elevated NfL can indicate nerve-cell injury but cannot, by itself, identify the underlying neurological condition.
• Age, kidney function, coexisting diseases and other factors can also affect biomarker levels, creating a risk of false-positive or false-negative results.

2. High costs and limited infrastructure

• Advanced immunoassays, mass spectrometry and specialised molecular testing may require expensive equipment, trained personnel and reliable laboratory infrastructure.
• These requirements can limit access in district hospitals and rural areas.

3. Lack of standardisation

• Differences in sample handling, laboratory methods, calibration, reference ranges and reporting practices can lead to inconsistent results.
• Harmonised protocols and external quality assurance are essential for reliable interpretation.

4. Limited validation across populations

• A biomarker developed using one population may perform differently in another because of differences in genetics, age, diet, comorbidities, environmental exposures and healthcare access.
• Indian populations need appropriate validation studies before imported diagnostic thresholds can be assumed to work reliably in routine clinical practice.

5. Ethical and social concerns

• Identifying disease-associated changes in asymptomatic individuals can create uncertainty and psychological distress, particularly when the marker indicates risk rather than a definite diagnosis.
• Genetic and health data may also be vulnerable to misuse, unauthorised disclosure or discriminatory practices. Strong privacy safeguards and clear communication about uncertainty are therefore essential.

6. The gap between discovery and clinical use

• A biomarker that performs well in a research study may not necessarily improve patient outcomes in routine healthcare.
• Clinical adoption requires evidence of analytical validity, clinical validity and clinical utility, along with appropriate regulatory assessment.

Way Forward

• Promote indigenous research and development. Support Indian biotechnology companies, research institutions and startups in developing affordable diagnostic reagents, assays, biosensors and testing platforms.
• Establish robust validation and quality standards. ICMR, CDSCO and relevant scientific and laboratory bodies should support evidence-based clinical guidance, reference standards, external quality assessment and transparent reporting of diagnostic performance.
• Expand access beyond metropolitan centres. Strengthen district-level laboratory capacity, referral networks, trained personnel and quality-assured point-of-care technologies where appropriate.
• Build population-specific evidence. Integrate genomic, clinical, environmental and lifestyle information from diverse Indian populations while ensuring that research findings are validated in independent cohorts.
• Safeguard personal data. Apply strong consent, access-control, security and data-governance practices consistent with applicable Indian law. Patients should receive clear explanations of what a result can—and cannot—establish.
• Connect testing with clinical decisions. Biomarker programmes should demonstrate that their use improves diagnosis, treatment selection, patient outcomes or cost-effectiveness rather than simply increasing the number of tests performed.
• Improve public awareness and professional training. Clinicians and patients need accessible guidance on the meaning of risk markers, the possibility of false results and the importance of clinical interpretation.

Conclusion

Chemical biomarkers are helping transform healthcare by enabling more precise assessment of disease, biological ageing and treatment response. Advances in neurological diagnostics demonstrate the potential of molecular testing to make disease evaluation less invasive and more accessible.

For India, the opportunity lies in combining initiatives such as GenomeIndia and the BHARAT Study with indigenous diagnostic innovation, rigorous clinical validation and equitable healthcare delivery.

The ultimate goal should not merely be to detect molecular changes earlier, but to translate reliable biomarker evidence into better health outcomes while protecting privacy, affordability and public trust.