Relationship Between Lipid Profile, Oxidative Stress Biomarkers, and Dermatochalasis Severity: A Cross-Sectional Study

1. Introduction

Dermatochalasis is a common age-associated disorder of the upper eyelid characterized by redundant, lax, and overhanging eyelid skin that may progress from a cosmetic concern to a functionally significant condition [1,2]. Although traditionally regarded as a local manifestation of periocular aging, population-based evidence indicates that dermatochalasis is not merely a passive consequence of chronological age. In the Rotterdam Study, moderate-to-severe sagging eyelids were observed in 17.8% of 5578 participants, with independent determinants including age, male sex, lighter skin color, higher body mass index, and genetic predisposition, suggesting a multifactorial biological basis beyond mechanical skin redundancy alone [3]. Histopathological studies further support this by demonstrating elastolysis, lymphatic vessel alterations, collagen disorganization, and macrophage-associated subclinical inflammation in dermatochalasis specimens [4,5]. These findings imply that dermatochalasis may represent a measurable phenotype of periocular connective-tissue degeneration rather than an isolated anatomic deformity.

The clinical relevance of this condition is substantial. Redundant upper eyelid skin can impair the superior visual field, induce eyelid heaviness and ocular discomfort, contribute to compensatory frontalis overactivity and headache, and negatively affect self-perceived appearance and quality of life [6,7]. Upper eyelid blepharoplasty is therefore performed not only for aesthetic rejuvenation but also for functional rehabilitation. Evidence-based reviews have shown that upper eyelid surgery can improve visual field, vision-related symptoms, headache burden, and health-related quality of life in appropriately selected patients [6,7]. However, surgery addresses the final structural expression of the disease rather than the biological processes that lead to eyelid tissue degeneration. Identification of systemic or modifiable biological factors associated with dermatochalasis could therefore improve risk stratification, clarify disease mechanisms, and potentially provide new preventive or disease-modifying perspectives.

Oxidative stress is a central mechanism in intrinsic and extrinsic skin aging [8]. It reflects a disruption of redox homeostasis in which oxidant generation exceeds antioxidant defense capacity, resulting in altered redox signaling and molecular damage [9]. Human skin is particularly vulnerable to oxidative injury because of continuous exposure to ultraviolet radiation, environmental pollutants, mitochondrial reactive oxygen species, and inflammatory mediators [10]. At the dermal level, oxidative stress promotes matrix metalloproteinase activation, collagen fragmentation, elastin degradation, and impaired extracellular matrix remodeling, processes that closely resemble the histological abnormalities observed in dermatochalasis [4,5,11]. The periocular region may be especially susceptible because eyelid skin is thin, highly dynamic, and chronically exposed to environmental stressors. Despite this biological plausibility, however, the relationship between systemic oxidative stress and dermatochalasis presence or severity has not been adequately defined.

Assessment of oxidative stress in clinical research is challenging because individual oxidant or antioxidant molecules may fluctuate and may not reflect the global redox burden. Total oxidant status (TOS) and total antioxidant status (TAS) provide integrated measures of circulating oxidant load and antioxidant capacity, respectively [12,13].

Lipid metabolism is another biologically plausible pathway linking systemic health to eyelid tissue aging. Low-density lipoprotein-cholesterol (LDL-C) cholesterol is not only a cardiovascular risk marker but also a substrate for oxidative modification. Oxidized LDL (ox-LDL) participates in oxidative injury, endothelial dysfunction, macrophage activation, and chronic low-grade inflammation [14]. Conversely, high-density lipoprotein-associated mechanisms, including paraoxonase-1 (PON 1) activity and apolipoprotein A1 (Apo A1) function, contribute to antioxidant and anti-inflammatory defense by limiting lipoprotein oxidation and modulating inflammatory signaling [15,16]. These pathways are highly relevant to dermatochalasis because macrophage-associated inflammation, extracellular matrix disruption, and elastin/collagen degeneration are already recognized histopathological features of the disease [4,5]. Nevertheless, whether lipid profile parameters and oxidative lipid-related biomarkers are associated with dermatochalasis severity remains insufficiently investigated.

The present study was designed to address this gap by evaluating the relationship between lipid profile, oxidative stress biomarkers, and dermatochalasis severity in a demographically balanced adult cohort. By examining conventional lipid parameters together with TOS, TAS, OSI, ox-LDL, PON 1, and Apo A1, this study aims to provide a biologically grounded framework for understanding dermatochalasis as a systemic-metabolic and oxidative stress-related phenotype of periocular aging.

2. Materials and Methods

2.1. Study Design and Participants

This cross-sectional study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the University of Health Sciences Antalya Training and Research Hospital (approval number: 2025-85). Written informed consent was obtained from all participants before enrollment.

A total of 300 adults aged 40-60 years who presented to the ophthalmology outpatient clinic were included. To minimize demographic imbalance, participants were evenly distributed by sex and age category: 150 women and 150 men, and 150 participants aged 40-50 years and 150 participants aged 51-60 years. Eligible participants were randomly selected from among individuals who met the study criteria.

Dermatochalasis severity was graded clinically according to the Jacobs classification [3]. Participants were divided into four groups: Grade 0, no dermatochalasis/control group (n=120); Grade 1, mild dermatochalasis with upper eyelid skin touching the eyelashes (n=60); Grade 2, moderate dermatochalasis with eyelid skin covering the eyelashes (n=60); and Grade 3, severe dermatochalasis with redundant upper eyelid skin overhanging the ocular surface (n=60).

To reduce confounding from systemic inflammation, metabolic disease, medication use, or environmental exposure, the exclusion criteria were strict. Individuals with systemic or ocular disease, active inflammatory or infectious conditions, previous eyelid or intraocular surgery, smoking history, current medication use, antioxidant supplementation, or vitamin supplementation were excluded. Furthermore, individuals working predominantly indoors were preferentially included to minimize the potential influence of chronic ultraviolet exposure.

2.2. Biochemical Measurements

Venous blood samples were obtained from all participants after a 12-hour overnight fast. Samples were collected into vacuum serum tubes, held at room temperature for 30 minutes, and centrifuged at 4100 rpm for 10 minutes. Serum was separated and stored at -80 °C until analysis. Hemolyzed or lipemic samples were excluded.

Routine lipid parameters, including high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), triglyceride (TG), very low-density lipoprotein (VLDL), and total cholesterol (TC), were measured on the same day using a Beckman AU5800 automated biochemical analyzer (Beckman Coulter, Brea, CA, USA) and commercial reagents from the same manufacturer. Because fasting TG levels were below 400 mg/dL in all participants, LDL-C was calculated using the Friedewald formula [17].

TOS and TAS were measured using commercially available automated colorimetric assay kits (Rel Assay Total Antioxidant Level Test Kit and Rel Assay Total Oxidant Level Test Kit, MegaTıp, Gaziantep, Türkiye). The oxidative stress index (OSI) was calculated as the ratio of TOS to TAS and expressed as arbitrary units, reflecting the global oxidant-antioxidant balance [OSI (arbitrary units) = (TOS, µmol H₂O₂ eq/L) / (TAS, µmol Trolox eq/L)] [12,13]. PON1 activity was measured using an automated kinetic method (Rel Assay PON 1 Test Kit, MegaTıp). Ox-LDL (Rel Assay Ox-LDL Test Kit, MegaTıp) and Apo A1 (Rel Assay Apo A1 Test Kit, MegaTıp) levels were assessed using quantitative enzyme-linked immunosorbent assay kits according to the manufacturer’s instructions.

3. Results

3.1. Participant Characteristics

A total of 300 participants were included in this study. The cohort was deliberately balanced according to sex and age groups, with 150 men and 150 women, and 150 participants in each age stratum of 40-50 and 51-60 years. The mean age of the entire sample was 49.75±6.33 years. According to dermatochalasis severity, 120 participants were classified as Grade 0, constituting the control group, while 60 participants were included in each of the Grade 1, Grade 2, and Grade 3 groups. There were no significant differences among the four groups in terms of age or sex distribution, confirming that the study groups were demographically comparable (Table 1).

3.2. Lipid Profile

In comparison of participants with and without dermatochalasis, LDL-C was significantly higher in the dermatochalasis group, whereas TC was significantly lower. However, both of these findings had small effect sizes. HDL-C, TG, and VLDL did not differ significantly between these two groups (Table 2).

Table 2. Lipid profile according to dermatochalasis presence.

Biomarker	Control median (IQR)	Dermatochalasis median (IQR)	p value	Effect size r	Magnitude
HDL-C	57.00 (50.40–65.90)	56.00 (47.75–66.78)	0.239	−0.080	Trivial/small
LDL-C	107.00 (87.50–125.50)	112.00 (95.00–136.00)	0.048	0.135	Small
TG	124.50 (93.80–182.00)	124.00 (90.56–159.10)	0.426	−0.054	Trivial
VLDL	24.90 (18.76–36.40)	24.80 (18.11–31.82)	0.426	−0.054	Trivial
TC	218.00 (192.44–244.00)	207.00 (189.00–230.00)	0.042	−0.139	Small

Mann–Whitney U test. Effect size r represents rank-biserial correlation. A p-value of <0.05 was considered statistically significant. High density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), triglyceride (TG), very low-density lipoprotein (VLDL), and total cholesterol (TC).

Table 2. Lipid profile according to dermatochalasis presence.

Biomarker	Control median (IQR)	Dermatochalasis median (IQR)	p value	Effect size r	Magnitude
HDL-C	57.00 (50.40–65.90)	56.00 (47.75–66.78)	0.239	−0.080	Trivial/small
LDL-C	107.00 (87.50–125.50)	112.00 (95.00–136.00)	0.048	0.135	Small
TG	124.50 (93.80–182.00)	124.00 (90.56–159.10)	0.426	−0.054	Trivial
VLDL	24.90 (18.76–36.40)	24.80 (18.11–31.82)	0.426	−0.054	Trivial
TC	218.00 (192.44–244.00)	207.00 (189.00–230.00)	0.042	−0.139	Small

Mann–Whitney U test. Effect size r represents rank-biserial correlation. A p-value of <0.05 was considered statistically significant. High density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), triglyceride (TG), very low-density lipoprotein (VLDL), and total cholesterol (TC).

Table 3. Oxidative stress and antioxidant biomarkers according to dermatochalasis presence.

Biomarker	Control median (IQR)	Dermatochalasis median (IQR)	p value	Effect size r	Magnitude
TOS	2.99 (1.76–4.76)	3.98 (2.39–5.84)	<0.001	0.238	Small-to-moderate
TAS	1.32 (1.13–1.46)	1.32 (1.17–1.44)	0.722	0.024	Trivial
OSI	1.18 (0.23–3.19)	2.98 (1.72–4.57)	<0.001	0.500	Moderate-to-large
PON1	323.72 (149.65–461.30)	268.49 (130.76–419.00)	0.045	−0.137	Small
Ox-LDL	40.76 (29.52–88.06)	43.97 (27.58–86.53)	0.518	−0.044	Trivial
ApoA1	8.98 (4.98–20.05)	13.07 (7.40–26.24)	0.013	0.169	Small

Mann–Whitney U test. Effect size r represents rank-biserial correlation. A p-value of <0.05 was considered statistically significant.TOS: total oxidant status; TAS: total antioxidant status; OSI: oxidative stress index; PON1: paraoxonase-1; ox-LDL: oxidized LD; ApoA1: apolipoprotein A1.

Table 3. Oxidative stress and antioxidant biomarkers according to dermatochalasis presence.

Biomarker	Control median (IQR)	Dermatochalasis median (IQR)	p value	Effect size r	Magnitude
TOS	2.99 (1.76–4.76)	3.98 (2.39–5.84)	<0.001	0.238	Small-to-moderate
TAS	1.32 (1.13–1.46)	1.32 (1.17–1.44)	0.722	0.024	Trivial
OSI	1.18 (0.23–3.19)	2.98 (1.72–4.57)	<0.001	0.500	Moderate-to-large
PON1	323.72 (149.65–461.30)	268.49 (130.76–419.00)	0.045	−0.137	Small
Ox-LDL	40.76 (29.52–88.06)	43.97 (27.58–86.53)	0.518	−0.044	Trivial
ApoA1	8.98 (4.98–20.05)	13.07 (7.40–26.24)	0.013	0.169	Small

Mann–Whitney U test. Effect size r represents rank-biserial correlation. A p-value of <0.05 was considered statistically significant.TOS: total oxidant status; TAS: total antioxidant status; OSI: oxidative stress index; PON1: paraoxonase-1; ox-LDL: oxidized LD; ApoA1: apolipoprotein A1.

When lipid parameters were evaluated across dermatochalasis severity grades, total cholesterol showed a statistically significant grade-wise difference with a small effect size. LDL-C did not differ significantly across severity groups in unadjusted nonparametric analysis, but it later emerged as the only independent predictor of increasing dermatochalasis severity in ordinal logistic regression (Table 4 and Table 5).

3.3. Oxidative Stress and Antioxidant Biomarkers

Oxidative stress markers showed a more robust association with dermatochalasis than conventional lipid parameters. TOS and OSI values were significantly higher in participants with dermatochalasis than in the control group. Among all evaluated biomarkers, OSI demonstrated the largest effect size, indicating that global oxidant-antioxidant imbalance was the strongest biochemical feature associated with dermatochalasis presence.

PON 1 activity was significantly lower in the dermatochalasis group, while Apo A1 levels were significantly higher. TAS and ox-LDL did not differ significantly between the groups. Across severity grades, OSI remained the most consistent oxidative stress parameter, showing a significant grade-wise difference with a moderate effect size (Table 3 and Table 4).

3.4. Correlation and Regression Analyses

Spearman correlation analysis showed that dermatochalasis grade was positively correlated with LDL-C, TOS, OSI, and Apo A1. The OSI had the strongest correlation with disease grade among all measured biomarkers (Table 4).

In multivariate binary logistic regression, OSI, LDL-C, and TC values were independent predictors of dermatochalasis. The OSI was the strongest independent predictor, with each unit increase associated with higher odds of dermatochalasis. LDL-C was also independently associated with disease presence, whereas total cholesterol showed an inverse independent association.

In ordinal logistic regression, LDL-C was the only independent predictor of increasing dermatochalasis severity. The OSI was strongly associated with disease presence but did not independently predict severity after adjustment. This finding suggests a differential biological pattern: oxidative imbalance appears to be more closely linked to disease presence, whereas LDL-C may be more relevant to severity progression (Table 5).

3.5. Diagnostic Performance

ROC analysis confirmed the OSI as the best-performing biomarker for distinguishing participants with dermatochalasis from the control group. The OSI achieved an AUC of 0.750, with 91.11% sensitivity and 55.00% specificity at a cut-off value of ≥1.24. This indicates acceptable discriminatory performance, mainly driven by high sensitivity.

TOS, Apo A1, TC, PON 1, and LDL-C also had statistically significant ROC results, but their AUC values were below 0.70, limiting their standalone diagnostic utility. Therefore, the OSI appears to be the most informative single biomarker for dermatochalasis presence, whereas LDL-C provides additional value as the only independent marker associated with both disease presence and severity (Table 6).

4. Discussion

This study provides new evidence that dermatochalasis is associated with a measurable systemic oxidative-lipid imbalance rather than being merely a passive anatomic consequence of aging. The principal finding was that oxidative stress, particularly as expressed by the OSI, showed the strongest independent association with dermatochalasis presence and the best diagnostic performance among all evaluated biomarkers. In contrast, LDL-C was the only parameter independently associated with both dermatochalasis presence and increasing disease severity. This separation between disease presence and disease severity is the central message of the present study: oxidative imbalance appears to characterize the biological onset of dermatochalasis, whereas LDL-related lipid metabolism may be more relevant to disease progression.

Dermatochalasis has traditionally been conceptualized as an age-related degenerative eyelid disorder driven by skin laxity, gravity, and local connective-tissue attenuation [2,18]. However, this explanation is incomplete. Population-based data from the Rotterdam Study showed that sagging eyelids are influenced not only by age but also by sex, body mass index, skin phenotype, and genetic predisposition, supporting a multifactorial biology [3]. Histopathological studies further shifted the field away from a purely mechanical model by demonstrating elastolysis, lymphatic abnormalities, collagen disorganization, and macrophage-associated subclinical inflammation in tissues affected by dermatochalasis [4,5]. Our findings extend this literature by showing that these local tissue changes are accompanied by systemic biochemical signals, most notably increased OSI values. Therefore, the present study supports a broader interpretation of dermatochalasis as a visible periocular phenotype of connective-tissue aging shaped by oxidative stress and lipid biology.

The strongest finding of this study was the consistent association between the OSI and dermatochalasis presence. OSI values were significantly higher in patients with dermatochalasis than in the control group; they showed the largest effect size among all biomarkers, remained the strongest independent predictor in multivariate logistic regression, and achieved the highest discriminatory value in ROC analysis. This finding is biologically plausible. Oxidative stress is a key driver of both intrinsic and extrinsic skin aging, and the thin periocular skin is particularly vulnerable because of its structural delicacy, high mobility, and chronic environmental exposure [9,10]. Reactive oxygen species activate redox-sensitive signaling pathways, increase matrix metalloproteinase activity, impair collagen synthesis, fragment dermal collagen, and promote elastin degeneration [11,19,20]. These mechanisms mirror the core histological findings reported in dermatochalasis, including elastic fiber loss, collagen disruption, lymphatic dysfunction, and inflammatory cell infiltration [4,5]. Thus, the present results provide a mechanistic bridge between systemic oxidative burden and the local tissue architecture of dermatochalasis.

A major finding of this study is that the OSI, rather than TOS or TAS alone, emerged as the most informative marker. This distinction is important. Oxidative stress is not simply the presence of oxidants or the absence of antioxidants; it is the imbalance between oxidant load and antioxidant defense [9]. TOS and TAS individually provide partial information, whereas the OSI captures the net redox disequilibrium [12,13]. In our cohort, TAS alone did not differ significantly between groups, and TOS showed a weaker association than the OSI. This suggests that dermatochalasis is better characterized by a global oxidant-antioxidant imbalance than by isolated changes in either oxidative load or antioxidant capacity. The high sensitivity of the OSI in ROC analysis further supports its potential value as a screening or risk-stratification biomarker, although its modest specificity limits its use as a standalone diagnostic test.

A second major finding is the role of LDL-C, which was independently associated with dermatochalasis presence and was the only independent predictor of increasing severity in ordinal logistic regression. This finding is clinically important because it suggests that the biology of dermatochalasis may not be homogeneous across disease stages. Oxidative stress may act as an initiating or permissive factor, whereas lipid-related mechanisms may influence the degree of tissue degeneration after disease onset. LDL-C is a biologically active lipoprotein that can undergo oxidative modification, promote macrophage activation, and amplify chronic low-grade inflammation [14,21]. In the eyelid, such mechanisms could plausibly contribute to extracellular matrix remodeling, lymphatic dysfunction, and progressive dermal laxity. The fact that LDL-C predicted severity even when the OSI did not remain significant in the ordinal model supports the conclusion that lipid metabolism may be more relevant to progression than to initiation.

Our findings must also be interpreted against apparently conflicting evidence from the literature on lipid and oxidative biomarkers. First, although LDL-C was associated with disease presence and severity, ox-LDL was not significantly different between the groups and did not predict dermatochalasis. At first glance, this may seem contradictory because ox-LDL is often considered a marker of oxidative lipid injury [14,21]. However, circulating ox-LDL is only one component of a complex lipid-oxidation network. It may not accurately reflect tissue-level oxidative modification in the periocular dermis, local macrophage activation, or HDL-related antioxidant dysfunction. Moreover, oxidized phospholipids and modified ApoA1 particles may provide more refined information than total circulating ox-LDL in some disease states [22,23]. Therefore, the lack of an association between ox-LDL and dermatochalasis does not weaken the oxidative-lipid hypothesis; rather, it suggests that conventional circulating ox-LDL may be insufficiently sensitive for this specific tissue phenotype.

Second, TC showed an inverse independent association with dermatochalasis presence, whereas LDL-C showed a positive association. This apparently paradoxical result should be interpreted cautiously. TC is a composite measure that does not distinguish between lipoprotein subfractions, particle size, lipid trafficking, HDL function, or local tissue lipid handling. Skin lipid biology is highly compartmentalized: cholesterol and other lipids are essential for epidermal barrier function, lamellar body formation, and cutaneous homeostasis [24,25]. Therefore, serum TC may not parallel the biologically relevant lipid processes occurring in eyelid skin. The divergent behavior of LDL-C and TC in our model may indicate that dermatochalasis is linked not to global cholesterol excess but rather to specific lipoprotein patterns or lipid-oxidation pathways. This is precisely why LDL-C remained clinically meaningful while TC functioned as a nonspecific composite marker.

Third, PON1 activity was lower and ApoA1 levels were higher in dermatochalasis patients, while HDL-C did not differ significantly. This pattern is consistent with the current understanding that HDL quantity and HDL function are not equivalent. PON1 is an HDL-associated enzyme that contributes to antioxidant and anti-inflammatory HDL activity, including protection against LDL oxidation [15,16,26]. Reduced PON1 activity in the dermatochalasis group may therefore indicate impaired HDL antioxidant function despite unchanged HDL-C concentrations. The increase in ApoA1, although initially counterintuitive, may represent a compensatory response to oxidative stress or a marker of altered HDL remodeling. ApoA1 can undergo oxidative modification, and dysfunctional HDL may lose anti-inflammatory capacity or even become pro-inflammatory under oxidative and inflammatory conditions [23,27]. Thus, the combination of lower PON1, higher ApoA1, and unchanged HDL-C suggests that functional lipoprotein quality may be more relevant than routine lipid concentration in dermatochalasis.

The present study differs from prior research on dermatochalasis in three important ways. First, most previous studies focused on clinical severity, functional visual impairment, surgical outcomes, or histopathology [4,5,6,7]. These studies established the clinical and tissue-level importance of dermatochalasis but did not define systemic biochemical correlates. Second, studies of skin aging have extensively implicated oxidative stress, collagen degradation, elastosis, and lipid-barrier dysfunction, but these findings have rarely been translated into a dermatochalasis-specific biomarker framework [10,11,19,20,24]. Third, unlike studies evaluating a single oxidative or lipid parameter, thisstudy has assessed a broader panel including routine lipids, TOS, TAS, OSI, ox-LDL, PON1, and ApoA1, with the application of both binary and ordinal regression. This allowed us to distinguish predictors of disease presence from predictors of severity. That distinction is the major conceptual strength of the present study.

The clinical implications of these findings should be interpreted with appropriate restraint. Dermatochalasis is a common reason for upper eyelid blepharoplasty, and functional surgery improves the visual field, symptoms, and quality of life in selected cases [6,7]. However, surgical correction does not address the upstream biological mechanisms. If oxidative stress and LDL-related lipid biology are confirmed in prospective studies, these markers could help in identifying individuals at higher risk for earlier or more progressive dermatochalasis. The OSI may be useful as a sensitive risk marker for disease presence, while LDL-C may help to identify patients more likely to develop higher-grade tissue redundancy. At this stage, these findings should not be interpreted as evidence that antioxidant supplementation or lipid-lowering therapy prevents dermatochalasis. Rather, they lead to a biologically testable hypothesis: redox imbalance and LDL-related lipoprotein biology may be modifiable pathways in periocular tissue aging.

This study has several strengths. The cohort was relatively large for a biomarker-based dermatochalasis study and was deliberately balanced by sex and age category, reducing two major demographic sources of confounding. Strict exclusion criteria minimized the influence of smoking, systemic disease, active inflammation, medication use, antioxidant supplementation, and previous ocular or eyelid surgery. The study evaluated both conventional lipid parameters and mechanistically relevant oxidative stress biomarkers. The statistical approach was also clinically informative: nonparametric group comparisons were supported by effect sizes, correlation analyses, multivariate binary regression, ordinal regression for severity, and ROC analysis for diagnostic performance. Importantly, the study did not rely solely on p values; it identified which biomarkers were statistically significant, independently predictive, and diagnostically informative.

However, the limitations should also be acknowledged. First, the cross-sectional design prevents causal inference. Elevated OSI and LDL-C values may contribute to dermatochalasis, but they may also reflect biological changes associated with the condition. Longitudinal studies are required to determine whether these biomarkers precede disease onset or predict progression. Second, the strict inclusion criteria increased the study’s internal validity but may limit the generalizability to older patients, smokers, and patients with diabetes, metabolic syndrome, and chronic inflammatory disease or those receiving lipid-lowering or antioxidant therapy. Third, dermatochalasis severity was assessed using a clinical grading system. Although practical and reproducible in routine ophthalmic practice, clinical grading may not capture three-dimensional eyelid volume, skin thickness, brow position, levator function, or quantitative visual-field impact. Fourth, serum biomarkers may not fully reflect local oxidative stress or lipid metabolism within eyelid tissue. Future studies combining serum markers with eyelid tissue analysis would provide stronger mechanistic evidence. Finally, although the OSI showed acceptable discrimination, its specificity was modest; therefore, the OSI should be considered a potential component of a multimodal risk model rather than a standalone diagnostic test.

Future research should move in three directions. First, prospective longitudinal studies should test whether baseline OSI and LDL-C values predict incident dermatochalasis or progression from mild to moderate/severe disease. Second, tissue-level studies should evaluate whether serum OSI values correlate with local eyelid markers such as matrix metalloproteinase expression, collagen fragmentation, elastin loss, lymphatic dilation, macrophage infiltration, PON1 activity, ox-LDL, Apo A1, and lipidemic profiles. Third, predictive models integrating clinical risk factors, standardized eyelid photography, quantitative visual-field testing, serum OSI, and LDL- and HDL-function markers should be developed and externally validated. Such models could redefine dermatochalasis from a purely surgical endpoint to a biologically stratified periocular aging phenotype.

5. Conclusions

This study demonstrates that dermatochalasis is strongly associated with systemic oxidative imbalance, particularly elevated OSI values, and that the OSI provides the best diagnostic performance among evaluated biomarkers. LDL-C was the only parameter independently associated with both disease presence and severity, suggesting that oxidative stress may be linked primarily to disease development, whereas LDL-related lipid biology may contribute to progression. These findings support a new conceptual framework in which dermatochalasis is not merely an age-related eyelid redundancy but a clinically visible manifestation of redox-lipid dysregulation in periocular connective-tissue aging. Prospective and tissue-level studies are warranted to determine whether OSI and LDL-C values can serve as predictive biomarkers or therapeutic targets in dermatochalasis.