Meibomian gland dysfunction in geriatric population: tehran geriatric eye study

Epidemiology and Risk Factors of Dry Eye Disease: Considerations for Clinical Management

Dry eye disease is a multifactorial condition characterised by tear film instability, hyperosmolarity and ocular surface inflammation. Understanding the epidemiology of dry eye disease and recognising both modifiable and non-modifiable risk factors can assist eye care practitioners in assessing, treating, and managing patients with the condition. This review considers current knowledge surrounding its incidence and prevalence, as well as associated demographic, systemic, ocular, and iatrogenic, and lifestyle-related modifiable risk factors. Population-based prevalence estimates vary according to the diagnostic criteria used to define dry eye disease, as well as severity and demographic characteristics of the population. Considering recent data and variable population demographics, conservative prevalence estimates suggest that 10-20% of the population over 40 years of age report moderate to severe symptoms and/or seek treatment for dry eye disease. Individuals with specific non-modifiable demographic risk factors may be at increased risk of developing dry eye disease. Advanced age, female sex and East Asian ethnicity have been identified as key non-modifiable demographic features predisposing individuals to dry eye disease. Systemic conditions that have been associated with an increased risk of dry eye disease include migraine, Sjögren syndrome, connective tissue disorders, mental health disorders, diabetes mellitus and androgen deficiency. Medications that may contribute to this risk include antidepressants, antihistamines, and hormone replacement therapy. Ocular and iatrogenic risk factors of dry eye disease include blepharitis, Demodex infestation, ocular surgery, blink completeness, contact lens wear, and topical ophthalmic medications. A range of modifiable lifestyle factors that can increase the risk of dry eye disease have also been identified, including low humidity environments, digital screen use, quality of sleep, diet, and eye cosmetic wear. Dry eye is a common disease affecting millions globally. Increasing knowledge regarding its associated risk factors can better prepare the eye care practitioner to successfully manage patients with this ocular surface disease.

Sex Differences in the Prevalence of Meibomian Gland Dysfunction: A Mini Review

PURPOSE

In this review, we aimed to investigate the literature on sex-specific prevalence of meibomian gland dysfunction (MGD) and to determine whether women or men are more at risk for MGD.

METHODS

A search was conducted on PubMed using the terms: (Sex OR Gender OR prevalence) AND (Meibomian gland).

RESULTS

Twenty-four relevant studies on MGD prevalence were identified, including 10 population-based and 14 hospital-based studies. Among the population-based studies, five studies reported higher rates among men, three studies found no differences, and one study observed higher rates among women. In the hospital-based studies, 10 studies reported no difference, two found higher rates among men, and one found higher among women. In the reviewed literature, there was a considerable variation between studies in terms of quality, sample size, age ranges, diagnostic criteria.

CONCLUSIONS

While most of the population-based studies suggest a higher prevalence among men, the majority of clinic-based studies show no significant difference. Further research with larger samples and standardized criteria is needed to determine whether men are indeed more susceptible to MGD.

Risk Factors for Meibomian Gland Disease Assessed by Meibography

Purpose

To elucidate risk factors for meibomian gland disease (MGD) and understand associated changes in meibography and in relation to ocular surface disease.

Patients and Methods

As part of the standard workup for ocular surface disease at a tertiary academic center, 203 patients received an ocular history and lifestyle questionnaire. The questionnaire included detailed inquiries about ocular health and lifestyle, including makeup use, cosmetic eyelid procedures, screen time, and contact lens habits. Subjects also took the standardized patient evaluation of eye dryness (SPEED) II questionnaire. Meibomian gland (MG) dropout and structural changes were evaluated on meibography and scored by three independent graders using meiboscores. Statistical analysis was conducted to identify significant risk factors associated with MG loss.

Results

This retrospective, cross-sectional study included 189 patients (378 eyes) with high-quality images for grading, and the average age was 67 years (77% female). Patients older than 45 years had significantly more dropout than younger patients (p < 0.01). Self-reported eye makeup use did not significantly impact MG loss. Patients with a history of blepharoplasty trended toward higher meiboscores, but the difference was not statistically significant. Self-reported screen time did not affect meiboscores. Contact lens use over 20 years was associated with significant MG loss (p < 0.05). SPEED II scores had no relationship to meiboscores (p = 0.75).

Conclusion

Older age is a significant risk factor for MG loss. Any contact lens use over 20 years also impacted MG dropout. Highlighting the incongruence of symptoms to signs, SPEED II scores showed no relationship to the structural integrity of MGs.

Dysregulation of Lipid Metabolism in Aging Meibomian Glands and Its Molecular Markers

The main function of exocrine Meibomian glands (MGs) is to produce a lipid-rich secretion called meibum which plays a critical role in maintaining the ocular surface homeostasis of humans and most mammals. The chemical composition of meibum, and its quantity produced by MGs, largely determine whether it can fulfill its role successfully. Aging was frequently associated with the onset of various MG-related pathologies. The goal of this study was to determine how aging affects the chemical composition and quantity of meibum in mice, and identify possible molecular markers of aging. Unbiased, untargeted and targeted lipidomic evaluation of mouse MG lipids was conducted using liquid chromatography-high-resolution mass spectrometry, and the results were analyzed using Principal Component, Orthogonal Projections to Latent Structures Discriminant, and Partial Least Square Discriminant Analyses. We found that aging leads to dysregulation of lipid metabolism in MGs, changing the ratios of major classes of MG lipids (such as wax esters, triacylglycerols, and phospholipids) in a progressive manner. Several lipid species that belong to these groups of MG lipids are proposed as clear markers of aging in a mouse model.

Impacts of gender and age on meibomian gland in aged people using artificial intelligence

Purpose: To evaluate the effects of age and gender on meibomian gland (MG) parameters and the associations among MG parameters in aged people using a deep-learning based artificial intelligence (AI). Methods: A total of 119 subjects aged ≥60 were enrolled. Subjects completed an ocular surface disease index (OSDI) questionnaire, received ocular surface examinations including Meibography images captured by Keratograph 5M, diagnosis of meibomian gland dysfunction (MGD) and assessment of lid margin and meibum. Images were analyzed using an AI system to evaluate the MG area, density, number, height, width and tortuosity. Results: The mean age of the subjects was 71.61 ± 7.36 years. The prevalence of severe MGD and meibomian gland loss (MGL) increased with age, as well as the lid margin abnormities. Gender differences of MG morphological parameters were most significant in subjects less than 70 years old. The MG morphological parameters detected by AI system had strong relationship with the traditional manual evaluation of MGL and lid margin parameters. Lid margin abnormities were significantly correlated with MG height and MGL. OSDI was related to MGL, MG area, MG height, plugging and lipid extrusion test (LET). Male subjects, especially the ones who smoke or drink, had severe lid margin abnormities, and significantly decreased MG number, height, and area than the females. Conclusion: The AI system is a reliable and high-efficient method for evaluating MG morphology and function. MG morphological abnormities developed with age and were worse in the aging males, and smoking and drinking were risk factors.

TFOS lifestyle: Impact of societal challenges on the ocular surface

Societal factors associated with ocular surface diseases were mapped using a framework to characterize the relationship between the individual, their health and environment. The impact of the COVID-19 pandemic and mitigating factors on ocular surface diseases were considered in a systematic review. Age and sex effects were generally well-characterized for inflammatory, infectious, autoimmune and trauma-related conditions. Sex and gender, through biological, socio-economic, and cultural factors impact the prevalence and severity of disease, access to, and use of, care. Genetic factors, race, smoking and co-morbidities are generally well characterized, with interdependencies with geographical, employment and socioeconomic factors. Living and working conditions include employment, education, water and sanitation, poverty and socioeconomic class. Employment type and hobbies are associated with eye trauma and burns. Regional, global socio-economic, cultural and environmental conditions, include remoteness, geography, seasonality, availability of and access to services. Violence associated with war, acid attacks and domestic violence are associated with traumatic injuries. The impacts of conflict, pandemic and climate are exacerbated by decreased food security, access to health services and workers. Digital technology can impact diseases through physical and mental health effects and access to health information and services. The COVID-19 pandemic and related mitigating strategies are mostly associated with an increased risk of developing new or worsening existing ocular surface diseases. Societal factors impact the type and severity of ocular surface diseases, although there is considerable interdependence between factors. The overlay of the digital environment, natural disasters, conflict and the pandemic have modified access to services in some regions.

Identifying Meibomian Gland Dysfunction Biomarkers in a Cohort of Patients Affected by DM Type II

(1) Background: Meibomian gland dysfunction (MGD) among patients with diabetes mellitus (DM) is a common manifestation of dry eye syndrome (DES). (2) Methods: The purpose of this study is to identify clinical parameters and biomarkers useful to improve the follow-up and the treatment of these patients. We have used an ocular surface disease index (OSDI) questionnaire, Schirmer test I/II, tear film break-up time (TF-BUT), fluorescein plus lissamine green staining, Marx's line (ML), and meibomian gland (MGs) morphology using Sirius^® Topographer (CSO, Costruzione Strumenti Oftalmici, Florence, Italy). Blood sample analysis included glucose, glycated hemoglobin, lipid profile, cortisol, dehydroepiandrosterone sulfate (DHEA-S), androstenedione (ASD) and testosterone. (3) Results: Cortisol and ASD were positively correlated with an increase of MG tortuosity, and an Increased level of triglycerides was associated with a reduction of MGs length. DHEAS levels lowered with age and were associated with ocular surface staining. (4) Conclusions: Future studies, perhaps including meibum lipid analysis and tear cytokine levels, may also further elucidate the connection between these parameters, MG architecture and function.

Meibomian Gland Morphology Changes After Cataract Surgery: A Contra-Lateral Eye Study

Purpose: To evaluate the morphology changes of meibomian glands (MGs) after cataract surgery. Setting: Hangzhou Branch of the Eye Hospital of Wenzhou Medical University, Zhejiang, China. Methods: In this contra-lateral eye study, 40 patients received unilateral cataract surgery for age-related cataract. All the patients underwent the evaluation of non-invasive break-up time (NIBUT) and lower tear meniscus height (TMH) before the surgery and 6 months post-operatively. The MGs were evaluated via ImageJ and Meibomian Gland Bio-image Analyzer. MG dropout, length, width, area, gland diameter deformation index (DI), and gland signal index (SI) were recorded. Results: MG length, width, area, DI, and SI were significantly decreased after cataract surgery in the study group (operated eyes, P < 0.001, P = 0.003, P < 0.001, P = 0.001, and P < 0.001, respectively) and showed no significant changes in the control group (non-operated eyes) (all P > 0.05). MG loss increased more in the study group (P = 0.030), and the changes in TMH and NIBUT were not significantly different between the two eyes (both P > 0.05). Conclusion: Cataract surgery aggravated meibomian gland morphology, such as MG loss, MG length, width, area, and SI, and produced no change in NIBUT and TMH at 6 months post-operatively.