Keratoconus is a bilateral, often asymmetric, progressive corneal ectatic disorder characterized by progressive thinning and steepening of the cornea, resulting in irregular astigmatism and visual impairment(Gomes et al., 2022). Traditionally regarded as a rare disease with a prevalence of approximately 1 in 2,000 individuals, recent epidemiological studies employing advanced corneal imaging techniques have reported markedly higher rates, ranging from 1 in 375 to 1 in 2,000, and reaching up to 4.79% in certain populations(Godefrooij et al., 2017);(Staff, n.d.);(Kobia-Acquah et al., 2022). The condition typically manifests during the second decade of life and demonstrates a more aggressive course in younger patients(Smadja & Krauthammer, 2023).

The imperative of early detection cannot be overstated. Timely diagnosis facilitates corneal cross-linking, currently the only intervention proven to arrest disease progression(Hafezi et al., 2026). Moreover, recognition of subclinical keratoconus is essential in the preoperative screening of candidates for laser refractive surgery, as performing surgery on undiagnosed ectatic corneas may precipitate severe iatrogenic ectasia(Saad et al., 2023). Despite significant advances in diagnostic modalities, the identification of subclinical and forme fruste keratoconus eyes with apparently normal topography but keratoconus in the fellow eye remains a considerable challenge(Consejo et al., 2021);(Naujokaitis et al., 2024).

This review seeks to provide a comprehensive synthesis of the earliest markers of keratoconus, systematically categorizing them into ocular biomarkers (derived from corneal imaging and genetic analysis) and systemic biomarkers (reflecting inflammatory, oxidative, hormonal, and systemic associations). By delineating the spectrum of early indicators, this review aims to inform clinicians and researchers of the most promising strategies for early detection, while simultaneously highlighting critical gaps that warrant further investigation.

2. Ocular Markers: Detecting Keratoconus in the Eye

2.1 Corneal Tomography: The Current Gold Standard

Scheimpflug-based corneal tomography, exemplified by the Pentacam (Oculus), remains the gold standard and most sensitive modality for keratoconus detection. Unlike conventional topography, which is limited to anterior surface mapping, tomography provides comprehensive three-dimensional data, including anterior and posterior corneal elevations, pachymetry, and corneal volume(Elbendary & Abou Samra, 2013).

Key tomographic indices for early detection include:

• Belin/Ambrósio Enhanced Ectasia Display (BAD_D): Demonstrates excellent discriminatory ability, with a cutoff of 1.8 yielding 81% specificity and 80% sensitivity for early KC. In certain studies, the area under the receiver operating characteristic curve (AUC) reached 1.000 in differentiating keratoconus from normal corneas(Quanchareonsap et al., 2024).
• Posterior corneal elevation: Abnormalities in the posterior surface often precede anterior changes. The posterior curvature symmetry index (cutoff 0.16) achieved 97% specificity and 67% sensitivity for early KC(Pircher et al., 2025).
• Tomographic and Biomechanical Index (TBI): A combined index (cutoff 0.59) with 95% specificity and 77% sensitivity, representing one of the most robust parameters for early identification(Ganesh et al., 2024).

Despite its diagnostic power, tomography faces limitations in detecting early ectasia, particularly in forme fruste keratoconus, where topography remains normal. This challenge has prompted exploration of complementary modalities.

2.2 Corneal Epithelial Thickness Mapping: Revealing Early Remodeling

Epithelial remodeling represents one of the earliest biological responses to biomechanical weakness. The epithelium thins over the cone apex and thickens peripherally, producing a characteristic “doughnut pattern.” This compensatory mechanism can mask topographic abnormalities, making epithelial mapping critical for detecting disease before tomographic changes emerge(Wang et al., 2025).

Key epithelial parameters:

• Inter-zonal thickness differences: A study of 189 eyes showed significantly increased inferior-temporal differences in both keratoconic eyes and tomographically normal fellow eyes, with AUC values of 0.991 and 0.749, respectively(Naujokaitis et al., 2024).
• Epithelial thickness standard deviation: Demonstrated high diagnostic efficiency (AUC = 0.982, sensitivity 97.4%, specificity 92.1%). Combining multiple epithelial variables improved detection in topography-normal eyes (AUC = 0.896)(X. Chen et al., 2023).
• Bowman’s layer thickening: Emerging evidence suggests Bowman’s layer thickening may precede epithelial thinning, indicating a possible temporal sequence: Bowman’s thickening → epithelial thinning → topographic changes(Masiwa & Moodley, 2020).

2.3 Corneal Biomechanics: Functional Assessment

Keratoconus is fundamentally a biomechanical disorder, characterized by reduced rigidity and increased deformability. Biomechanical assessment provides functional insights that may detect disease before structural changes appear.

Key technologies and parameters:

• Ocular Response Analyzer (ORA): Measures corneal hysteresis (CH) and corneal resistance factor (CRF), both reduced in KC(Wang et al., 2025).
• Corvis ST: Provides dynamic corneal response parameters, including deformation amplitude, applanation velocities, and the Corvis Biomechanical Index (CBI).
• Combined indices: Integration of biomechanical and tomographic data significantly improves diagnostic accuracy. AI models combining anterior curvature with biomechanics achieved an AUC of 0.985, further enhanced to 0.991 with the addition of CBI(Roszkowska et al., 2025).

2.4 Artificial Intelligence and Machine Learning

Artificial intelligence (AI) has emerged as a transformative tool in early keratoconus detection. Deep learning applied to tomographic maps demonstrates high accuracy in differentiating normal, subclinical, and manifest KC.

Key findings:

• AI models using anterior curvature alone achieved an AUC of 0.938 (90.8% sensitivity, 96.9% specificity)(Quanchareonsap et al., 2024).
• Adding dynamic corneal response parameters improved performance to an AUC of 0.985.
• Incorporating the Corvis Biomechanical Index further enhanced accuracy to an AUC of 0.991(Miao et al., 2023).

These results highlight the potential of AI to refine diagnostic decision-making, particularly in borderline cases.

2.5 Optical Coherence Tomography (OCT)

Optical coherence tomography (OCT) provides high-resolution cross-sectional imaging, enabling detailed evaluation of corneal layers.

Key applications:

• Epithelial thickness profiling: Fourier-domain OCT detects subtle epithelial changes indicative of early KC(Naujokaitis et al., 2024).
• Bowman’s layer assessment: OCT facilitates measurement of Bowman’s thickness, reinforcing its role as a potential early biomarker(Pircher et al., 2025).
• Stromal analysis: Regional stromal thickness metrics, combined with Scheimpflug data, may outperform epithelial parameters alone in differentiating subclinical KC(Pircher et al., 2025).

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3. Genetic Markers: The Molecular Blueprint

Genetic factors are increasingly recognized as central to the pathogenesis of keratoconus. Although fewer than 10% of patients report a positive family history, genetic associations provide critical insights into disease mechanisms and potential biomarkers for early detection.

Key genetic findings: A systematic review and meta-analysis prioritized eight single-nucleotide polymorphisms (SNPs) across six genes/loci in White populations. Five of these loci were initially identified in genome-wide association studies, including FOXO1 (rs2721051). Such associations may enhance understanding of disease biology and facilitate the discovery of molecular markers for early diagnosis and monitoring of progression(Rong et al., 2017).

4. Systemic Markers: The Body’s Role in Keratoconus

Emerging evidence increasingly supports the view that keratoconus is not solely an ocular disorder but one with systemic dimensions. Associations with systemic diseases, inflammatory mediators, oxidative stress, hormonal factors, and the microbiome provide important clues to pathogenesis and early detection strategies.

4.1 Systemic Disease Associations

A comprehensive review identified atopy, Down syndrome, and connective tissue disorders as the most frequently reported systemic associations(Unni & Lee, 2023).

• Atopy and allergic disease: Conditions such as allergic conjunctivitis, eczema, asthma, and hay fever are consistently linked to keratoconus. The association likely reflects a combination of chronic ocular surface inflammation, immune dysregulation, and mechanical trauma from eye rubbing a well-established risk factor(Zehra et al., 2024).
• Connective tissue disorders: Noninflammatory connective tissue diseases, including Marfan syndrome, Ehlers-Danlos syndrome, osteogenesis imperfecta, and mitral valve prolapse, suggest shared extracellular matrix abnormalities, particularly involving collagen metabolism(J. Chen et al., 2025).
• Down syndrome: Keratoconus prevalence is markedly higher in individuals with Down syndrome, likely due to connective tissue fragility and increased eye rubbing(Unni & Lee, 2023).
• Diabetes mellitus as a protective factor: Intriguingly, diabetes has been proposed as protective, potentially through advanced glycation end-products that stiffen the cornea or altered inflammatory profiles(Akowuah et al., 2022).

4.2 Inflammatory and Immune Biomarkers

Immune dysregulation is increasingly recognized as a driver of keratoconus onset and progression. Genetic predisposition may prime a dysregulated inflammatory response in the ocular surface and corneal microenvironment.

• Tear film biomarkers: Elevated levels of interleukins (IL‑1α, IL‑1β, IL‑4, IL‑5, IL‑6, IL‑8, IL‑17), TNF‑α, MMP‑9, HMGB1, ICAM‑1, and VCAM‑1 have been consistently reported. These findings underscore keratoconus as an inflammation-driven disorder, compounded by tear film instability and oxidative stress.
• Serum biomarkers: Systemic markers such as platelet-to-lymphocyte ratio (PLR) have been found elevated in keratoconus patients, whereas CRP/albumin ratio and neutrophil-to-lymphocyte ratio (NLR) showed no consistent differences(Pinheiro-Costa et al., 2023).

4.3 Oxidative Stress Biomarkers

Oxidative stress is a pivotal contributor to keratoconus pathophysiology. Elevated oxidative markers and reduced antioxidant defenses have been documented in tears, aqueous humor, and blood.

• Increased oxidative stress markers: Elevated malondialdehyde (MDA) and glutathione peroxidase 3 (GPX3) in tear fluid suggest potential roles as early biomarkers.
• Decreased antioxidants: Reduced antioxidant activity, including lower serum prolidase activity (PA), has been observed in keratoconus patients.
• Cellular dysregulation: Alterations in cellular antioxidant signaling pathways further implicate oxidative imbalance in disease progression.(Pinheiro-Costa et al., 2023);(Roszkowska et al., 2025)

4.4 Hormonal Markers

The onset of keratoconus during puberty and its exacerbation during pregnancy highlight the role of hormonal modulation.

• Gonadotropins (FSH and LH): Imbalances in follicle-stimulating hormone and luteinizing hormone have been implicated in disease onset.
• Prolactin-inducible protein (PIP): Regulated by sex hormones, PIP has been proposed as a novel biomarker, with altered androgen and estrogen profiles observed in keratoconus patients.
• HPG-axis hormones: Systematic reviews consistently link hypothalamic-pituitary-gonadal axis fluctuations with keratoconus development and progression(Pinheiro-Costa et al., 2023);(Karamichos, 2023).

4.5 Microbiome and the Gut–Eye Axis

Recent studies highlight the role of the gut–eye axis in ocular health. Alterations in the ocular surface microbiome may contribute to immune dysregulation in keratoconus.

• Distinct microbiome signatures have been correlated with disease severity and immune profiles.
• Dysbiosis of the ocular surface microbiome may sustain low-grade chronic inflammation.
• These findings suggest microbial factors may influence keratoconus pathogenesis, opening avenues for novel interventions(Kumar et al., 2025).

.1 A Multimodal Approach to Early Detection The earliest markers of keratoconus encompass a continuum from corneal microstructural changes to systemic biomarkers, underscoring the complex and multifactorial nature of the disease. No single parameter currently achieves perfect sensitivity and specificity for early detection. Instead, an integrated multimodal approach—combining complementary diagnostic modalities—offers the greatest promise. Proposed temporal sequence of early markers: 1. Genetic predisposition: SNPs such as FOXO1 variants establish baseline susceptibility(Bykhovskaya et al., 2016). 2. Systemic factors: Atopy, connective tissue disorders, hormonal fluctuations, and inflammatory/oxidative stress profiles create a permissive environment(Harrison et al., 1989). 3. Bowman’s layer thickening: Potentially the earliest detectable structural change(Pircher et al., 2025). 4. Epithelial remodeling: Thinning over the cone apex and compensatory peripheral thickening (“doughnut pattern”)(Naujokaitis et al., 2024). 5. Biomechanical weakening: Reduced rigidity and increased deformability(Miao et al., 2023). 6. Posterior corneal elevation: Abnormalities precede anterior surface changes. 7. Anterior topographic steepening: Detectable on corneal topography. 8. Clinical manifestations: Irregular astigmatism, Munson’s sign, and overt visual impairment. 5.2 Clinical Implications The identification of earliest markers carries several important clinical implications: • Screening high-risk populations: Adolescents with atopy, Down syndrome, connective tissue disorders, or family history should undergo regular corneal evaluation. Portable imaging may enable school-based screening in high-prevalence regions. • Pre-refractive surgery screening: Comprehensive corneal evaluation—including tomography, epithelial mapping, and biomechanics—is essential to exclude subclinical keratoconus and prevent iatrogenic ectasia. • Early intervention: Timely corneal cross-linking, particularly in young patients and high-risk ethnic groups, halts progression and optimizes outcomes. • Monitoring progression: Serial tomographic, epithelial, and biomechanical assessments enable precise tracking and timely therapeutic decisions. 5.3 Research Gaps and Future Directions Despite significant advances, several critical gaps remain: • Standardization of biomarkers: Variability in parameters and cutoffs across studies limits consensus. Prospective multicenter trials are needed. • Validation of systemic biomarkers: Tear film and serum markers require large-scale validation; the role of the microbiome warrants deeper exploration. • Longitudinal studies: Most data are cross-sectional; longitudinal designs are essential to establish temporal relationships. • Integration of multi-omics: Combining genetic, proteomic, metabolomic, and microbiome data with imaging may enable personalized risk stratification. • Therapeutic implications: Targeting inflammation, oxidative stress, or microbiome dysbiosis may open new avenues for prevention and disease modification.