Novel biomarkers in early disease detection

Corresponding author: Bandela Abhilash Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. Novel biomarkers in early disease detection Bandela Abhilash 1, *, Yerikala Ramesh 2, Venugopalaiah Penabaka 2 and Yadala Prapurna Chandra 3 1 IV Year B.Pharmacy, Ratnam Institute of Pharmacy, Pidathapolur (V &P), SPSR Nellore – 524 346. 2 Department of Pharmaceutics, Ratnam Institute of Pharmacy, Pidathapolur (V &P), SPSR Nellore – 524 346. 3 Department of Pharmacology, Ratnam Institute of Pharmacy, Pidathapolur (V &P), SPSR Nellore – 524 346. Bandela Abhilash : https://orcid.org/0009-0009-8598-5681 Yerikala Ramesh : https://orcid.org/0000-0002-8331-8190 GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 364–376 Publication history: Received on 20 September 2025; revised on 28 October 2025; accepted on 31 October 2025 Article DOI: https://doi.org/10.30574/gscbps.2025.33.1.0418 Abstract Detecting diseases at an early stage is crucial for improving survival rates, ensuring timely treatment, and minimizing healthcare burdens. Traditional diagnostic techniques, such as imaging and biochemical testing, often identify diseases only after symptoms become evident, which reduces their effectiveness in early diagnosis. In contrast, novel biomarkers have emerged as promising tools that enable detection of pathological alterations at the molecular and cellular level long before clinical signs appear. Biomarkers serve as quantifiable indicators of physiological or pathological processes and therapeutic responses. Advances in molecular biology, genomics, proteomics, and metabolomics have expanded the discovery of novel biomarkers, including circulating tumor DNA (ctDNA), microRNAs, exosomes, and specific metabolic patterns. These innovative indicators show great potential for the early identification of cancers, cardiovascular conditions, neurodegenerative diseases, and infectious disorders. Beyond early detection, novel biomarkers assist in disease risk evaluation, prognosis, and monitoring of treatment efficacy. Their growing use aligns with the principles of personalized and precision medicine, enabling tailored diagnostic and therapeutic strategies for individual patients. Nevertheless, the implementation of these biomarkers in clinical settings faces challenges, such as lack of validation, standardization issues, and regulatory constraints. Ongoing research and technological progress are essential to overcome these barriers and fully realize the potential of novel biomarkers in transforming early disease detection and enhancing global health outcomes. Keywords: Novel Biomarkers; Early Diagnosis; Molecular Detection; Precision Medicine; Disease Prognosis 1. Introduction Early disease detection is a cornerstone of effective healthcare, as timely diagnosis significantly improves treatment outcomes, reduces morbidity, and lowers healthcare costs. Traditional diagnostic methods, such as imaging, histopathological examination, and biochemical assays, though valuable, often detect diseases only after clinical symptoms appear. This delay can limit treatment options and decrease survival rates, particularly in conditions like cancer, cardiovascular disease, and neurodegenerative disorders. Hence, there is a growing need for advanced diagnostic tools that can identify diseases at their earliest molecular or cellular stages.1 GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 364–376 365 Biomarkersmeasurable biological indicators of normal or pathological processeshave emerged as powerful tools in this context. They can be derived from a variety of biological sources, including blood, urine, tissues, and other body fluids. Conventional biomarkers, while useful, often lack sensitivity or specificity for early-stage disease detection. Recent advancements in molecular biology, genomics, proteomics, and metabolomics have led to the discovery of novel biomarkers that offer greater precision, enabling the identification of disease-associated changes long before clinical manifestations occur2. These novel biomarkers not only enhance early diagnosis but also aid in risk assessment, disease classification, and monitoring therapeutic responses. For instance, circulating tumor DNA (ctDNA), microRNAs, and exosomes have shown tremendous potential in detecting cancers at subclinical stages. Similarly, protein-based and metabolic biomarkers are providing new insights into neurodegenerative and metabolic disorders3. The integration of novel biomarkers into diagnostic practice marks a shift toward personalized and predictive medicine, where interventions can be tailored to an individual’s unique molecular profile. As research progresses, the continued development and validation of novel biomarkers hold the promise of transforming early disease detection, ultimately improving patient prognosis and advancing precision healthcare4. 1.1. Importance of Early Disease Detection Early disease detection plays a vital role in improving clinical outcomes and enhancing the effectiveness of healthcare systems. Detecting diseases at their initial stages allows for timely intervention, which can significantly reduce morbidity, mortality, and overall treatment costs. In conditions such as cancer, cardiovascular disease, and neurodegenerative disorders, early diagnosis often determines the success of therapy and long-term survival rates. Traditional diagnostic approaches, including imaging and histopathological examinations, generally identify diseases only after symptoms become evident or when substantial tissue damage has occurred. This delay in detection limits therapeutic options and reduces the likelihood of achieving complete remission. Conversely, identifying molecular and cellularalterations before clinical manifestation enables the implementation of preventive or targeted therapeutic strategies5. Advancements in molecular biology, genomics, and bioinformatics have enabled the development of sensitive diagnostic tools capable of identifying subclinical disease markers. These innovations are paving the way for predictive and personalized medicine, allowing healthcare professionals to stratify patient risk, tailor treatments, and monitor disease progression more effectively. Ultimately, early disease detection not only improves patient prognosis but also reduces the socioeconomic burden of chronic diseases by minimizing the need for extensive and costly late-stage treatments 6. 1.2. Limitations of Conventional Diagnostic Methods Conventional diagnostic techniquessuch as imaging, biochemical assays, and histopathological examinations—have long served as essential tools in medical practice. While these approaches remain central to disease diagnosis, they possess several limitations that restrict their effectiveness in detecting diseases at early stages. A primary limitation is their inability to identify molecular changes preceding clinical symptoms. Many diseases, including cancer and neurodegenerative disorders, undergo lengthy asymptomatic phases during which cellular and molecular alterations occur. Traditional diagnostic tools typically detect abnormalities only once structural or functional damage is already significant, thereby delaying intervention7. Another limitation lies in their restricted sensitivity and specificity. Imaging methods such as X-rays, CT scans, and MRI can reveal anatomical abnormalities but may fail to distinguish between benign and malignant or early-stage lesions. Similarly, biochemical assays often measure nonspecific markers influenced by multiple physiological variables, which can lead to false-positive or false-negative results8. Furthermore, histopathological examinations, although considered the diagnostic gold standard for many diseases, are invasive and time-consuming. They depend heavily on tissue availability and pathologist interpretation, leading to potential subjectivity and inter-observer variability. These limitations not only delay diagnosis but also contribute to diagnostic errors and increased healthcare costs. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 364–376 366 Additionally, conventional diagnostics often lack predictive capability, offering limited insight into disease progression or therapeutic response. In contrast, emerging molecular and genomic technologies provide opportunities for earlier, more accurate, and personalized detection by identifying biomarkers that reflect disease activity at the molecular level9. Figure 1 Biomarker Categories and Domain 2. Biomarkers – an overview 2.1. Definition and Types of Biomarkers A biomarker (biological marker) is a measurable indicator of normal biological processes, pathogenic processes, or pharmacological responses to therapeutic interventions. Biomarkers can be molecules, genes, proteins, metabolites, or even imaging findings that objectively reflect physiological or disease states.10 According to the U.S. National Institutes of Health (NIH), biomarkers are classified into several types based on their function • Diagnostic biomarkers identify the presence of a disease or condition. • Prognostic biomarkers give details about how a condition is expected to progress or turn out. • The possibility of a response to a particular treatment is indicated by predictive biomarkers. • Pharmacodynamic or response biomarkers measure the biological response to a therapy. • Monitoring biomarkers are used to assess the status of a disease or treatment over time. Recent advances in genomics, proteomics, and metabolomics have expanded biomarker research, leading to the discovery of novel molecular biomarkers with high sensitivity and specificity for early disease detection11. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 364–376 367 2.2. Role of Biomarkers in Clinical Practice Biomarkers play a pivotal role in modern clinical medicine, supporting diagnosis, prognosis, disease monitoring, and personalized treatment strategies. In oncology, for example, biomarkers such as HER2 in breast cancer and EGFR mutations in lung cancer help tailor targeted therapies, improving patient outcomes12. In cardiovascular disease, cardiac troponins serve as gold-standard biomarkers for early detection of myocardial infarction. Similarly, biomarkers like amyloid-β and tau proteins are critical in diagnosing neurodegenerative diseases such as Alzheimer’s disease. Beyond diagnosis, biomarkers guide drug development and clinical trials by predicting therapeutic efficacy and toxicity, thus reducing the time and cost of drug discovery. The integration of biomarker-based diagnostics into clinical workflows represents a key component of precision and personalized medicine, allowing treatments to be customized to individual biological profiles 13. 3. Novel Biomarkers in Early Disease Detection Early disease detection is essential for improving clinical outcomes, enabling preventive interventions, and reducing healthcare costs. Conventional diagnostic methods often fail to identify diseases in their preclinical stages. Recent advancements in molecular biology and omics technologies have led to the discovery of novel biomarkers that can detect diseases at the molecular or cellular level long before symptoms appear. These include genetic, proteomic, metabolomic, epigenetic, and circulating biomarkers, which together form the foundation of precision medicine14. 3.1. Genetic Biomarkers (DNA, RNA, MICRORNAS) Genetic biomarkers involve alterations in DNA or RNA sequences that are associated with disease susceptibility, onset, or progression. Mutations, gene amplifications, and chromosomal rearrangements serve as key indicators in various cancers25.MicroRNAs (miRNAs)small non-coding RNAsregulate gene expression and are emerging as sensitive biomarkers for early detection of cancers, cardiovascular, and neurodegenerative diseases. For example, miR-21 and miR-155 are elevated in several cancers, offering diagnostic and prognostic value15. 3.2. Proteomic Biomarkers (Protein Expression Patterns) Proteomic biomarkers reflect changes in protein abundance, structure, or post-translational modification during disease development. These biomarkers are crucial because proteins directly mediate physiological functions. Advances in mass spectrometry and protein microarrays have enabled large-scale identification of disease-specific protein signatures. For instance, elevated levels of prostate-specific antigen (PSA) and CA-125 serve as indicators for prostate and ovarian cancers, respectively16. 3.3. Metabolomic Biomarkers (Metabolic Signatures) Metabolomic biomarkers involve the analysis of small-molecule metabolites that reflect biochemical changes within cells and tissues. Since metabolism is closely linked to cellular function, metabolic alterations can indicate disease at very early stages. Techniques such as nuclear magnetic resonance (NMR) and mass spectrometry (MS) help identify disease-specific metabolic signatures, such as altered glucose or lipid profiles in cancer and diabetes17. 3.4. Epigenetic Biomarkers (DNA Methylation, Histone Modifications) Epigenetic biomarkers are based on heritable changes in gene expression that occur without alterations in DNA sequence. These include DNA methylation and histone modification patterns, which can silence or activate genes involved in tumorigenesis. Aberrant methylation of tumor suppressor genes like BRCA1 or p16INK4a has been recognized as an early indicator of cancer development18. 3.5. Circulating Tumor Cells and Exosomes Circulating tumor cells (CTCs) and exosomes in blood are minimally invasive “liquid biopsy” tools that provide realtime information about tumor biology. CTCs offer insight into metastasis, while exosomes—nano-sized vesicles carrying DNA, RNA, and proteinsserve as rich sources of molecular biomarkers for early cancer detection. These circulating biomarkers enable continuous disease monitoring and early therapeutic intervention without the need for invasive procedures19. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 364–376 368 Figure 2Novel biomarkers in early disease detection 4. Applications of Novel Biomarkers in Specific Diseases 4.1. Cancer Cancer remains a leading cause of morbidity and mortality worldwide, and early detection significantly improves therapeutic success and survival rates. The development of novel biomarkers has transformed oncology by enabling non-invasive, precise, and early diagnosis. Figure 3 Applications of Novel Biomarkers in cancer Genomic biomarkers such as BRCA1/2 mutations identify individuals with hereditary breast and ovarian cancer risk, allowing for preventive interventions. Circulating tumor DNA (ctDNA) and cell-free DNA (cfDNA) have emerged as minimally invasive liquid biopsy tools capable of detecting genetic and epigenetic alterations associated with tumor presence and evolution20. Serum biomarkers, including carcinoembryonic antigen (CEA), CA-125, and prostate-specific antigen (PSA), are routinely used in clinical diagnostics, although their specificity for early detection is limited. Recent advancements in microRNA (miRNA) profilingfor example, upregulation of miR-21, miR-155, and miR-210offer promising avenues for early tumor detection, especially when integrated with high-throughput screening platforms. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 364–376 369 The advent of multi-omics approaches combining genomics, transcriptomics, and proteomics has further enhanced biomarker accuracy, allowing for better disease stratification, monitoring therapeutic responses,andguiding precision oncology21. 4.2. Cardiovascular Diseases Globally, cardiovascular diseases (CVDs) continue to be the leading cause of death.Traditional diagnostic tools such as ECG and imaging detect only overt structural or functional changes, whereas biomarkers reveal early pathophysiological alterations at the molecular level. Cardiac troponins (cTnI and cTnT) are the gold standard biomarkers for myocardial infarction, indicating cardiomyocyte necrosis with high specificity and sensitivity. B-type natriuretic peptide (BNP) and N-terminal proBNP (NT-proBNP) are key biomarkers for heart failure, correlating with ventricular stress and disease severity22. Beyond these, high-sensitivity C-reactive protein (hs-CRP) reflects vascular inflammation and predicts cardiovascular risk, while galectin-3, ST2, and growth differentiation factor-15 (GDF-15) are emerging markets for myocardial fibrosis, cardiac remodeling, and heart failure prognosis. Novel omics-driven biomarkers, including specific lipidomic and metabolomic profiles, are being studied for early detection of atherosclerosis and subclinical CVD, paving the way for predictive cardiology23. Figure 4 Cardiovascular diseses 4.3. Neurodegenerative Disorders Neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS) are characterized by progressive neuronal damage, often detected only after significant cognitive or motor impairment. Cerebrospinal fluid (CSF) biomarkers including amyloid-β42 (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau) are well-established indicators of AD pathology, correlating with amyloid deposition and neurofibrillary tangles24. Neurofilament light chain (NFL), measurable in both CSF and blood, is an emerging biomarker reflecting axonal damage across multiple neurodegenerative disorders. In PD, α-synuclein aggregates, particularly phosphorylated or oligomeric forms, are under investigation as diagnostic and progression markers. Recent advancements in plasma-based biomarkers and exosomal profiling have enabled less invasive detection, supporting early diagnosis and longitudinal disease monitoring. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 364–376 370 Integration of these biomarkers with neuroimaging and genetic testing holds potential for preclinical detection and personalized therapeutic strategies25. Figure 5 Neurodegenerative Disorders 4.4. Infectious Diseases The global burden of infectious diseases underscores the need for rapid, accurate, and early diagnostics. Biomarkers facilitate the distinction between bacterial and viral infections, guide treatment selection, and monitor therapeutic response. Procalcitonin (PCT) and C-reactive protein (CRP) remain the most widely used biomarkers for bacterial infection and sepsis, assisting clinicians in antibiotic stewardship. In viral infections, detection of specific nucleic acids such as HIV RNA, HBV DNA, or HCV RNA serves as direct molecular biomarkers for infection status and viral load quantification. Figure 6 Infectious Diseases During the COVID-19 pandemic, markers like interleukin-6 (IL-6), D-dimer, C-reactive protein, and ferritin were critical in identifying severe inflammatory responses and predicting clinical outcomes. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 364–376 371 Emerging technologies such as proteomics, metabolomics, and host-response signatures are uncovering pathogenspecific biomarkers that could revolutionize early detection and outbreak control26. 5. Techniques for Biomarker Detection Biomarker detection techniques are essential for identifying molecular signatures that indicate physiological or pathological conditions. These methods are broadly classified into molecular, proteomic, and metabolomic platforms. 5.1. Molecular Techniques Molecular techniques are primarily used for detecting gene expression, genetic mutations, and nucleic acid quantification. The most commonly used molecular methods include: 5.1.1. Polymerase Chain Reaction (PCR) PCR and its variants (RT-PCR, qPCR) amplify specific DNA or RNA sequences, allowing for sensitive and specific detection of genetic markers associated with diseases27. 5.1.2. Next-Generation Sequencing (NGS) This high-throughput sequencing method enables comprehensive analysis of genetic variations, transcriptomes, and epigenetic changes, useful in cancer genomics and precision medicine. 5.1.3. Microarrays DNA and RNA microarrays allow simultaneous analysis of thousands of genes, facilitating gene expression profiling and biomarker discovery in diseases such as cancer and cardiovascular disorders28. 5.2. Proteomic and Metabolomic Platforms Proteomic and metabolomic techniques identify and quantify proteins and metabolites that reflect the functional state of biological systems. 5.2.1. Mass Spectrometry (MS) A key analytical tool in proteomics and metabolomics, MS enables high-resolution detection and quantification of biomolecules. When combined with separation techniques such as liquid chromatography (LC-MS) or gas chromatography (GC-MS), it provides insights into protein modifications, metabolic pathways, and disease mechanisms29. 5.2.2. Two-Dimensional Gel Electrophoresis (2D-GE) Commonly used in proteomic analysis, it separates proteins based on isoelectric point and molecular weight before identification by MS. Together, these techniques contribute significantly to precision diagnostics, drug development, and personalized medicine by providing a deeper understanding of molecular and biochemical alterations in disease states30. 5.3. Imaging-Based Biomarker Detection Imaging-based biomarker detection is a powerful approach used to visualize and quantify biological processes in living organisms. It enables non-invasive assessment of molecular and cellular changes associated with disease onset, progression, and therapeutic response. Biomarkers detected through imaging techniques provide crucial insights for early diagnosis, personalized medicine, and real-time monitoring of treatment efficacy31. This technique combines molecular imaging technologies with specific probes or contrast agents that target biomarkers such as proteins, receptors, or metabolic pathways. Common imaging modalities include magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), single-photon emission computed tomography (SPECT), and optical imaging. Each method provides distinct informationPET and SPECT reveal metabolic or functional activity, while MRI and CT offer high-resolution anatomical details. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 364–376 372 Imaging biomarkers are widely used in oncology, neurology, and cardiology. For instance, fluorodeoxyglucose (FDG) in PET imaging helps detect metabolic activity in cancer cells, while amyloid PET imaging assists in diagnosing Alzheimer’s disease. In cardiovascular diseases, MRI can identify tissue perfusion and viability, serving as a reliable biomarker for ischemic damage. Optical imaging using fluorescent and bioluminescent probes is also gaining attention for preclinical research due to its sensitivity and safety32. Recent advances have focused on developing multimodal imaging probes, which integrate multiple imaging capabilities (e.g., PET/MRI or CT/optical), providing comprehensive structural and functional data. Nanotechnology-based contrast agents, such as quantum dots and gold nanoparticles, have further enhanced signal sensitivity and specificity. Artificial intelligence and machine learning are now being integrated into imaging analysis to automatically detect and quantify biomarkers from complex datasets. Despite its advantages, imaging-based biomarker detection faces challenges such as high cost, limited accessibility, and the need for standardized quantification methods. Continued research aims to develop safer, more precise imaging agents and improve image processing algorithms to achieve better clinical translation33. 6. Clinical Significance and Challenges Enzyme-based biomarker detection is a cornerstone of modern diagnostic science, allowing for the precise identification and quantification of biological molecules associated with diseases. Enzymes, due to their high catalytic efficiency and specificity, serve as biological recognition elements that can detect minute changes in biomarker concentration. Clinically, these assays are applied in diagnosing cancer, cardiovascular disorders, diabetes, and infectious diseases. Despite their diagnostic value, the transition from research to clinical application faces several challenges. Factors such as enzyme instability, interference from biological matrices, and variations in sample preparation can reduce assay performance. Furthermore, the lack of standardization among laboratories complicates result interpretation. Ensuring reproducibility and robustness across diverse populations and healthcare settings remains an ongoing challenge. Therefore, continued efforts in assay optimization, validation, and integration with digital diagnostic platforms are crucial for clinical success34. 6.1. Sensitivity and Specificity Issues The diagnostic accuracy of enzyme-based assays is primarily determined by their sensitivity and specificity. Sensitivity ensures that even trace levels of biomarkers are detected, enabling early disease diagnosis and monitoring. Specificity, on the other hand, prevents false-positive outcomes by ensuring that only the target molecule reacts. However, challenges such as enzyme degradation, cross-reactivity with similar molecules, and variations in assay calibration can compromise these parameters. Advanced techniques like fluorescence resonance energy transfer (FRET), electrochemical biosensing, and nanomaterial-assisted enzyme immobilization are being explored to enhance sensitivity and selectivity. The combination of enzyme systems with microfluidics and AI-driven data interpretation has also improved diagnostic precision35. 6.2. Cost and Accessibility One of the major barriers to widespread adoption of enzyme-based biomarker detection is its cost. The expense of highpurity reagents, sophisticated analytical instruments, and the requirement for skilled operators increase overall diagnostic costs. In lowand middle-income countries, this limits routine clinical use. Recent research is focused on developing portable, cost-effective enzyme-based biosensors using paper-based or wearable platforms, which can provide rapid and reliable results at the point of care. Such innovations aim to bridge the gap between laboratory diagnostics and field-based applications, improving healthcare accessibility globally36. 6.3. Ethical and Regulatory Considerations Implementing enzyme-based biomarker assays in healthcare requires adherence to strict ethical and regulatory frameworks. Patient safety, informed consent, data confidentiality, and accurate result reporting are fundamental ethical concerns. Regulatory approval from authorities such as the U.S. FDA and the European Medicines Agency (EMA) ensures test quality, reliability, and safety before clinical deployment. Furthermore, equitable access to diagnostic technologies must be maintained to avoid disparities in healthcare. Continuous post-market surveillance and transparent communication of diagnostic outcomes strengthen public trust and uphold ethical standards37.