Types of Biomarkers: From Diagnostic Tools to Environmental Indicators

Biomarkers are measurable biological indicators that reflect what is happening inside a living system – whether that is a human body responding to disease, or an ecosystem under stress from pollutants. The National Institutes of Health defines a biomarker as any characteristic that can be objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacological responses to therapeutic interventions. What makes biomarkers so valuable across science and medicine is that they come in many forms and serve many purposes. Understanding how they are classified – based on their characteristics and their function – is foundational to appreciating their role in everything from detecting heart disease to monitoring water quality.

Biomarkers based on characteristics 🔗

One of the most widely used frameworks for classifying biomarkers groups them by what they measure and how they are detected. Under this system, biomarkers fall into three major categories: molecular biomarkers, cellular biomarkers, and imaging biomarkers.

Imaging biomarkers 🔗

Imaging biomarkers are detectable features captured through medical imaging technologies. They include characteristics such as lesion size, tissue density, contrast enhancement, and metabolic activity – all derived from scans rather than from laboratory samples. The three main imaging modalities used are CT, MRI, and PET scanning.

CT scans are particularly useful for detecting lung nodules and assessing coronary calcium as a marker for cardiovascular risk. MRI provides high-resolution images of soft tissues, making it the preferred tool for diagnosing musculoskeletal disorders and evaluating tumor dimensions. PET scans track glucose uptake in body tissues, which is valuable for assessing the metabolic activity of tumors and evaluating treatment response in oncology.

A key advantage of imaging biomarkers is that they are non-invasive and can capture whole-organ information in real time. As noted in a consensus statement published in Nature Reviews Clinical Oncology, imaging biomarkers are integral to routine cancer management and are used extensively in drug development and clinical trials – for example, the widely adopted RECIST criteria use tumor size measured on CT scans as a standard endpoint for evaluating treatment response.

Quantitative imaging biomarkers (QIBs) add another layer of precision. These are objective measurements derived from in vivo images on a ratio or interval scale, offering greater consistency for patient follow-up and clinical trials compared to qualitative assessments.

Molecular biomarkers 🔗

Molecular biomarkers are non-imaging markers with biophysical properties that allow measurement in biological samples such as blood, urine, cerebrospinal fluid, or biopsy tissue. The four main types of molecular biomarkers are genomic, transcriptomic, proteomic, and metabolic biomarkers.

Genomic biomarkers analyze DNA sequences – identifying single nucleotide polymorphisms (SNPs), copy number variations, epigenetic modifications, and mutations. DNA is chemically stable and easily detectable, making it an excellent biomarker source. Techniques like whole-genome sequencing (WGS), whole-exome sequencing (WES), and polymerase chain reaction (PCR) are routinely used for analysis. In cancer, somatic mutations – found only in tumor cells, not in healthy ones – serve as highly specific genomic targets.

Proteomic biomarkers focus on proteins. Blood-based protein biomarkers are widely used in diagnostic tests. A well-known example is cardiac troponin, which rises in the bloodstream following myocardial infarction, confirming heart muscle damage. Another example is prostate-specific antigen (PSA), used in prostate cancer screening. Proteins are informative because they directly reflect what genes are actively doing at any given moment.

Transcriptomic biomarkers examine gene expression patterns through RNA analysis, while metabolic biomarkers capture small molecules – lipids, amino acids, and other metabolites – that reflect the biochemical state of a cell or organism. Together, these molecular tools offer a comprehensive, multi-layered view of biological activity that imaging alone cannot provide.

Functional classification of biomarkers 🔗

A second major framework classifies biomarkers not by what they are, but by what they do – their clinical or applied purpose. The FDA-NIH Biomarker Working Group has defined seven functional categories: susceptibility and risk, diagnostic, monitoring, prognostic, predictive, pharmacodynamic and treatment response, and safety biomarkers. Each plays a distinct role in medical decision-making and environmental science.

Diagnostic biomarkers 🔗

Diagnostic biomarkers detect or confirm the presence of a disease or condition. They answer the question: does this person have the disease? Cardiac troponin for myocardial infarction and HER2 protein expression for breast cancer are both classic diagnostic biomarkers. In environmental science, blood lead levels serve as a diagnostic biomarker for environmental lead exposure – directly indicating whether an individual has been exposed to harmful concentrations of the metal.

Disease staging and prognostic biomarkers 🔗

Once a disease is confirmed, biomarkers help determine how advanced it is and what its likely course will be. Staging biomarkers classify disease severity; brain natriuretic peptide (BNP), for instance, is used to stage congestive heart failure. Prognostic biomarkers go further – they predict how a disease is likely to develop in an individual patient, regardless of treatment. In oncology, certain gene expression signatures can indicate whether a tumor is likely to remain localized or spread aggressively, helping clinicians and patients make informed decisions about the intensity of intervention needed.

Monitoring biomarkers 🔗

Monitoring biomarkers track changes in disease status over time or measure the body’s response to an intervention. HbA1c is a monitoring biomarker used to assess long-term blood glucose control in diabetes management. In pharmacology, pharmacodynamic (PD) biomarkers measure the direct interaction between a drug and its biological target – revealing whether the drug is achieving its intended effect at the molecular level.

Environmental biomarkers 🔗

In environmental science, biomarkers take on a different but equally important role: they are used to detect pollution, assess ecosystem health, and track the biological effects of contaminants on living organisms. Bioindicators – organisms whose physiological or population responses signal environmental change – are a well-established form of environmental biomarker. Lichens, for example, lack cuticles and roots, making them entirely dependent on atmospheric deposition. Their physiological parameters, including chlorophyll levels and photosynthesis rates, directly reflect air quality in an area. The presence of certain lichen species alone can indicate clean air, while their absence or degradation signals pollution.

In aquatic systems, biomarkers serve as early warning indicators of chemical stressors. Enzymatic biomarkers such as EROD (ethoxyresorufin-O-deethylase) activity in fish are used to detect exposure to polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs). Vitellogenin – a protein normally produced only in female fish – is detected in male fish exposed to estrogenic compounds, signaling endocrine disruption. Plankton are particularly sensitive to changes in water quality and serve as rapid-response environmental biomarkers in both freshwater and marine ecosystems.

Microbial communities also function as environmental biomarkers. Research has shown that specific bacterial groups such as Proteobacteria and Bacteroidetes can indicate water quality in rivers, while methanogens and methanotrophs signal anthropogenic activity in estuarine environments. These microbial shifts are highly sensitive and cost-effective indicators for large-scale pollution monitoring programs.

Emerging trends in biomarkers 🔗

The biomarker field is evolving rapidly, driven by advances in genomics, imaging technology, and artificial intelligence. The most significant shift is the transition toward precision medicine – an approach in which treatment decisions are tailored to the individual molecular profile of each patient’s disease rather than applying population-wide standards.

Biomarkers in cancer diagnostics 🔗

Cancer is at the center of this transformation. Research published in 2024 highlights how cancer biomarkers now fall into four functional roles: risk stratification, confirming disease presence, predicting disease trajectory, and classifying tumor subtypes for tailored treatment. This has shifted oncology away from defining cancers purely by organ of origin toward classifying them by their molecular characteristics – a fundamental change in how cancers are understood and treated.

Liquid biopsy is a major emerging tool in this space. Rather than requiring invasive tissue sampling, liquid biopsy analyzes circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and cell-free RNA from a blood sample. This allows early detection and real-time treatment monitoring for cancers such as lung and colorectal cancer, with far less burden for the patient than conventional biopsy.

Specific molecular targets are now directly guiding therapy selection. ALK and EGFR mutations in non-small cell lung cancer (NSCLC), KRAS mutations in colorectal cancer, and BRCA mutations in breast and ovarian cancer are examples of predictive molecular biomarkers that determine which targeted therapies are appropriate for a given patient. These are often paired with companion diagnostics – regulated tests that must confirm a biomarker’s presence before a specific drug can be prescribed.

Molecular biomarkers in therapeutic development 🔗

Clinical biomarker testing now drives drug development, not just diagnosis. By identifying which patients carry specific molecular targets, researchers can design clinical trials that are more efficient and ethically sound – enrolling only those patients most likely to benefit, rather than exposing everyone to experimental treatments. The TAPUR Study (Targeted Agent and Profiling Utilization Registry), for instance, is a basket trial that evaluates whether targeted therapies approved for one cancer type may also be effective in other cancers that share the same genetic mutation, regardless of where in the body the cancer originated.

Artificial intelligence is also reshaping biomarker discovery. AI and machine learning tools can mine large multi-omics datasets – integrating genomic, proteomic, and imaging data simultaneously – to identify subtle patterns that human analysis would miss. This is accelerating both the discovery of novel biomarkers and the development of diagnostics tools that are more accurate and scalable than ever before.

Digital and emerging biomarkers 🔗

Beyond the laboratory, a new category of digital biomarkers is gaining recognition. Collected through wearable devices and smartphones, these include physiological parameters such as heart rate variability, movement patterns, and speech characteristics. In Parkinson’s disease research, for example, finger-tapping patterns on a smartphone have been used as a non-invasive indicator of motor function decline. While still an emerging area, digital biomarkers represent a significant expansion of what counts as a measurable biological signal.

In environmental biotechnology, similar expansion is occurring. Biosensors – devices that detect biological responses to specific chemicals – are increasingly used alongside traditional biomarker assays to monitor pollutant exposure in aquatic organisms and industrial environments. The integration of these technologies with AI-driven analysis is making environmental monitoring faster, more sensitive, and more ecologically informative than traditional chemical assays alone.

What do you think? As molecular biomarkers move to the center of both cancer care and environmental monitoring, how should healthcare systems and regulatory bodies prioritize access to biomarker testing, especially in low-resource settings? And given that organisms like lichens and plankton are sensitive environmental biomarkers, what does their health – or decline – in your local environment tell you about the quality of the air and water around you?

References

1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884646/
2. https://pmc.ncbi.nlm.nih.gov/articles/PMC9884646/
3. https://en.wikipedia.org/wiki/Imaging_biomarker
4. https://www.nature.com/articles/nrclinonc.2016.162
5. https://en.wikipedia.org/wiki/Biomarker_(medicine)
6. https://www.mdpi.com/2563-6499/1/1/8
7. https://pmc.ncbi.nlm.nih.gov/articles/PMC10303887/
8. https://www.nature.com/scitable/knowledge/library/bioindicators-using-organisms-to-measure-environmental-impacts-16821310/
9. https://www.sciencedirect.com/science/article/pii/S1470160X20311468
10. https://pmc.ncbi.nlm.nih.gov/articles/PMC9654993/
11. https://pmc.ncbi.nlm.nih.gov/articles/PMC11571259/
12. https://pmc.ncbi.nlm.nih.gov/articles/PMC12468363/
13. https://pmc.ncbi.nlm.nih.gov/articles/PMC7616034/