Effect of smoking on the thickness of retinal layers in healthy smokers

Duman, Rahmi; Sabaner, Mehmet Cem; Çetinkaya, Ersan

doi:10.1080/15569527.2017.1300162

Cited by 21 publications

(14 citation statements)

References 15 publications

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“…Some have suggested that these differences were driven by thicker inner and outer nuclear layers in males 49 . While smoking has been identified as a modifiable risk factor for AMD 5,50-53 , we did not find any association between macular retinal thickness and smoking at baseline, which is also consistent with previous reports 54,55 . Once adjusted for age, baseline differences in retinal thickness among eyes with a grade 0 were driven by patients from the Chr1-prot-del group.…”

Section: Discussionsupporting

confidence: 93%

Macular retinal thickness differs markedly in age-related macular degeneration driven by risk polymorphisms on chromosomes 1 and 10

Zouache

Bennion

Hageman

et al. 2020

Sci Rep

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The two most common genetic contributors to age-related macular degeneration (AMD), a leading cause of irreversible vision loss worldwide, are variants associated with CFH-CFHR5 on chromosome 1 (Chr1) and ARMS2/HTRA1 on chromosome 10 (Chr10). We sought to determine if risk and protective variants associated with these two loci drive differences in macular retinal thickness prior and subsequent to the onset of clinically observable signs of AMD. We considered 299 individuals (547 eyes) homozygous for risk variants or haplotypes on Chr1 or Chr10 exclusively (Chr1-risk and Chr10-risk, respectively) or homozygous for a neutral haplotype (Chr1-neu), for the protective I62 tagged haplotype (Chr1-prot-I62) or for the protection conferring CFHR1/3 deletion haplotype (Chr1-prot-del) on Chr1 without any risk alleles on Chr10. Among eyes with no clinically observable signs of AMD, the deletion of CFHR1/3, which is strongly protective against this disease, is associated with significantly thicker retinas in the perifovea. When controlling for age, Chr10-risk eyes with early or intermediate AMD have thinner retinas as compared to eyes from the Chr1-risk group with similar disease severity. Our analysis indicates that this difference likely results from distinct biological and disease initiation and progression events associated with Chr1- and Chr10-directed AMD.

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Section: Discussionsupporting

confidence: 93%

Macular retinal thickness differs markedly in age-related macular degeneration driven by risk polymorphisms on chromosomes 1 and 10

Zouache

Bennion

Hageman

et al. 2020

Sci Rep

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“…In this study, a total of 13 observational studies (7 case-control, 5 cross-sectional, and 1 prospective consecutive case series study) were included [16–28]. In the included studies, we identified a total of 614 smokers and 625 controls.…”

Section: Resultsmentioning

confidence: 99%

Effects of Cigarette Smoking on Retinal and Choroidal Thickness: A Systematic Review and Meta-Analysis

Yang

Huang

Yao

2019

Journal of Ophthalmology

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Background Cigarette smoking has been regarded as a risk factor for the incidence of a wide variety of chronic illness; however, its effect on thickness of the retina or choroid is still unknown. Methods A consummate literature search was conducted in PubMed and Embase up to January, 2018. The quantitative synthesis was conducted by Stata 12.0. Results A total of 13 observational studies were included in this meta-analysis. In this meta-analysis of all available observational studies, no significant effect of tobacco smoking on retinal or choroidal thickness change was detected. However, advanced analyses showed that smoking would influence the thickness of RNFL (average: SMD, −0.332; 95% CI, −0.637 to −0.027; inferior: SMD, −0.632; 95% CI, −1.092 to −0.172; and superior: SMD, −0.720; 95% CI, −0.977 to −0.463) and GCL (superior: SMD, −0.549; 95% CI, −0.884 to −0.215; inferior: SMD, −0.602; 95% CI, −0.938 to −0.265). Meanwhile, subgroup analyses demonstrated that the results based on studies in some regions (America and Africa) and cross-sectional studies showed a reduced choroidal thickness in smokers. No publication bias was detected in this study. Conclusion In conclusion, no significant effect of tobacco smoking on retinal or choroidal thickness change was detected. However, smoking would influence the thickness of RNFL and GCL. Future research on this field would help in the prevention and treatment of smoking-associated disorders.

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“…There are several studies on the effects of smoking on retinal vessels 73,74 , but this does not explain how they perform better than normal. Moreover, there are spectral domain optical coherence tomography studies which shows the thickness of retinal layers in healthy chronic smokers was not significantly different to those of healthy individuals 75,76 . Sex, age, and confounding factors were likely to improve predictions, in other words, a large number of men over 30 years of age were included in our study, resulting in uniform results and higher R 2 values.…”

Section: Discussionmentioning

confidence: 99%

Effects of Hypertension, Diabetes, and Smoking on Age and Sex Prediction from Retinal Fundus Images

Kim

Noh

Byun

et al. 2020

Sci Rep

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Retinal fundus images are used to detect organ damage from vascular diseases (e.g. diabetes mellitus and hypertension) and screen ocular diseases. We aimed to assess convolutional neural network (CNN) models that predict age and sex from retinal fundus images in normal participants and in participants with underlying systemic vascular-altered status. In addition, we also tried to investigate clues regarding differences between normal ageing and vascular pathologic changes using the CNN models. In this study, we developed CNN age and sex prediction models using 219,302 fundus images from normal participants without hypertension, diabetes mellitus (DM), and any smoking history. The trained models were assessed in four test-sets with 24,366 images from normal participants, 40,659 images from hypertension participants, 14,189 images from DM participants, and 113,510 images from smokers. The CNN model accurately predicted age in normal participants; the correlation between predicted age and chronologic age was R 2 = 0.92, and the mean absolute error (MAE) was 3.06 years. MAEs in test-sets with hypertension (3.46 years), DM (3.55 years), and smoking (2.65 years) were similar to that of normal participants; however, R 2 values were relatively low (hypertension, R 2 = 0.74; DM, R 2 = 0.75; smoking, R 2 = 0.86). In subgroups with participants over 60 years, the MAEs increased to above 4.0 years and the accuracies declined for all test-sets. Fundus-predicted sex demonstrated acceptable accuracy (area under curve > 0.96) in all test-sets. Retinal fundus images from participants with underlying vascular-altered conditions (hypertension, DM, or smoking) indicated similar MAEs and low coefficients of determination (R 2) between the predicted age and chronologic age, thus suggesting that the ageing process and pathologic vascular changes exhibit different features. Our models demonstrate the most improved performance yet and provided clues to the relationship and difference between ageing and pathologic changes from underlying systemic vascular conditions. In the process of fundus change, systemic vascular diseases are thought to have a different effect from ageing. Research in context. Evidence before this study. The human retina and optic disc continuously change with ageing, and they share physiologic or pathologic characteristics with brain and systemic vascular status. As retinal fundus images provide high-resolution in-vivo images of retinal vessels and parenchyma without any invasive procedure, it has been used to screen ocular diseases and has attracted significant attention as a predictive biomarker for cerebral and systemic vascular diseases. Recently, deep neural networks have revolutionised the field of medical image analysis including retinal fundus images and shown reliable results in predicting age, sex, and presence of cardiovascular diseases. Added value of this study. This is the first study demonstrating how a convolutional neural network (CNN) trained using retinal fundus images from normal participants meas...

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Effect of smoking on the thickness of retinal layers in healthy smokers

Abstract: The thickness of retinal layers in healthy smokers was similar to those of healthy individuals.

Cited by 21 publications

References 15 publications

Macular retinal thickness differs markedly in age-related macular degeneration driven by risk polymorphisms on chromosomes 1 and 10

Macular retinal thickness differs markedly in age-related macular degeneration driven by risk polymorphisms on chromosomes 1 and 10

Effects of Cigarette Smoking on Retinal and Choroidal Thickness: A Systematic Review and Meta-Analysis

Effects of Hypertension, Diabetes, and Smoking on Age and Sex Prediction from Retinal Fundus Images

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