Macrovascular and peripheral vascular complications of smoking have been known for years, but the effects of smoking on ocular hemodynamics have not been determined.1–5
Many methods have been described to assess the retinal circulation.6–12 However, these methods have disadvantages such as their invasive nature (except the stroboscopic fundus camera) and high variability of results. Furthermore, they may only be capable of measuring the larger retinal vessels, whereas capillary hemodynamics play a vital role in tissue oxygenation.
Optical coherence tomography angiography (OCTA) is a new, noninvasive imaging technique that uses motion contrast imaging to obtain high-resolution volumetric blood flow information, generating angiographic images in a matter of seconds.
Our main focus in this study was to investigate the acute effect of nicotine on macular microcirculation in healthy non-smokers using OCTA.
Patients and Methods
Eighteen young, healthy, non-smoker volunteers older than 18 years of age and 18 gender-matched controls (nine female/nine male in each group) were enrolled in the study. Both the study and control groups were selected from individuals who had no chronic ocular or systemic disease. The study protocol was approved by the Izmir University Medical Park Hospital institutional review board and ethics committee. The research adhered to the tenets of the Declaration of Helsinki, and detailed written informed consent was obtained from each participant before the study.
This is a randomized, placebo-controlled study. Exclusion criteria were nystagmus, corneal opacity, cataract, glaucoma, congenital or acquired retinal disorders, history of ocular trauma or surgery, diabetes mellitus, arterial hypertension, anemia, renal disease, cardiovascular disease, epilepsy, migraine, pregnancy, breastfeeding, chronic use of analgesics, antihistamines, decongestants, oral contraceptives and sildenafil, refractive spherical errors greater than 5 diopters (D), and cylinder errors greater than 3D.
Age, sex, systolic blood pressure (BP), and diastolic BP were recorded. A comprehensive ophthalmic examination was performed, including autorefractometry and keratometry, best-corrected visual acuity assessment, slit-lamp anterior segment examination, axial length (AL) measurement by IOLMaster (ver. 3.02; Carl Zeiss Meditec, Jena, Germany), intraocular pressure (IOP) measurement by Goldmann applanation tonometry, dilated fundus examination, and OCTA. Spherical equivalent (SE) was determined using the formula SE = S+C/2, in which C was cylindrical power and S was spherical power.
Subjects were administered either 4 mg of nicotine gum (Nicorette; McNeil AB, Helsingborg, Sweden) or a placebo gum (Biotene; Laclede, Rancho Dominguez, CA), which had a similar taste and appearance to the nicotine gum. Participants in both groups were asked not to consume any caffeine-containing beverages or chocolate for at least 24 hours before baseline OCTA measurements. All baseline OCTA scans were performed between 10:00 a.m. and 12:00 p.m. to avoid diurnal fluctuations. Both groups were instructed not to eat, drink, or take any medications until after the evaluations were completed. The participants were instructed to chew the nicotine or placebo gum continuously at a normal chewing rate for up to 1 hour. OCTA measurements were repeated 1 hour after the baseline measurements.
Optical Coherence Tomography Angiography Measurements
XR Avanti AngioVue spectral-domain OCTA (Software Version 2015.1.1.98; Optovue, Fremont, CA) obtains volumetric scans of 304 × 304 A-scans using a light source of 840 nm. The flow can be detected as a variation over time in the speckle pattern formed by the interference of light scattered from erythrocytes and adjacent tissue structures.13 All OCTA scans were obtained using a scanning area of 6 mm × 6 mm. In previous studies, a cut-off value of signal strength index was set at 40 or less.14 Scans with signal strength index of less than 60, motion artifacts, and poor quality were excluded from the study. The Optovue Angio-Vue system provides numerical data regarding flow area and vessel density. Automatic segmentation was performed to generate en face images of the superficial retinal capillary plexus (SCP) and deep retinal capillary plexus (DCP). The SCP, DCP, and outer retina were defined as in the study by Jia et al.15 The flow area was defined as the percentage of area occupied by vessels in a 6 mm × 6 mm square region of interest centered on the foveal avascular zone (FAZ). Angio-Vue software automatically outputs the flow area value within the region of interest (Figure 1A). Vessel density was calculated as the percentage of area occupied by vessels and microvasculature in the selected region. The vessel density was individually calculated in five regions (fovea, temporal, superior, nasal, and inferior) based on the Early Treatment Diabetic Retinopathy Study contour map (Figure 1B). To measure choriocapillaris (CC) flow area, a 6 mm × 6 mm macular angiogram of the CC layer was analyzed.15,16 Flow area of CC was calculated automatically as CC vessel area divided by the selected area (Figure 1C). FAZ and central foveal thickness (CFT) are measured automatically using OCTA (Figure 1D). Subfoveal choroidal thickness (SFCT) was defined as the distance between the hyperreflective line corresponding to the base of the RPE and the hyperreflective line corresponding to the chorioscleral interface. SFCT was measured three times by two independent observers with manual calipers in horizontal and vertical sections beneath the fovea and average values recorded for analysis.
Angio-Vue software automatically outputs the flow area value within the region of interest (A). Vessel density is calculated as the percentage area occupied by vessels and microvasculature in the selected region. Vessel density was separately calculated in five regions (fovea, temporal, superior, nasal, and inferior) based on the Early Treatment Diabetic Retinopathy Study contour map (B). Flow area of the choriocapillaris (CC) was calculated automatically as CC vessel areas divided by selected areas (C). Foveal avascular zone and central foveal thickness (CFT) are measured automatically using OCTA (D).
Statistical analyses were performed using SPSS for Windows 21.0 (SPSS Inc., Chicago, IL). For each continuous variable, normality was determined using Kolmogorov–Smirnov test. The Kolmogorov–Smirnov test showed a normal distribution for all parameters. Categorical variables were analyzed using chi-square test. Baseline OCTA measurements of the groups were compared by independent t-test. OCTA measurement parameters before and after gum chewing were analyzed with paired t-test. P value of less than .05 was considered statistically significant.
No significant difference was observed between the groups in terms of demographic parameters, IOP, SE, or AL (Table 1).
The Demographic and Clinical Characteristics of the Nicotine Gum-Chewing Groupand Placebo Group
Baseline macular flow area (superficial, deep, and CC), superficial and deep vessel density, and FAZ area measurements in the study and placebo groups showed no significant differences (P > .05 for all; independent t-test). There was no significant difference between baseline CFT and SFCT measurements in either group (P > .05 for all; independent t-test) (Table 2).
Macular Perfusion Parameters of Nicotine Gum-Chewing Group and Control Group at Baseline
Chewing nicotine gum caused significant reductions in macular flow area (superficial, deep, FAZ area, and CC) and SFCT. Superficial and deep vessel density in all regions were significantly lower after chewing nicotine gum when compared with baseline (P < .05 all; paired t-test). Chewing nicotine gum caused no significant change in CFT(Table 3).
Macular Perfusion Parameters of Nicotine Gum-Chewing Group at Baseline and 1 Hour After Nicotine Gum Chewing
In the control group, there were no significant differences in macular flow area (superficial, deep, and CC), FAZ area, or superficial and deep vessel density measurements taken 1 hour after chewing placebo gum compared with baseline (P > .05; paired t-test) (Table 4).
Macular Perfusion Parameters of Controls at Baseline and 1 Hour AfterOral Placebo Gum Chewing
Boxplot analyses representing macular flow area measurements (superficial, deep, and CC) and FAZ area in the study group are shown in Figures 2 and 3.
Boxplot analysis of macular flow area (superficial, deep, and choriocapillaris) and foveal avascular zone (FAZ) area in the study group at baseline.
Boxplot analysis of macular flow area (superficial, deep, and choriocapillaris) and foveal avascular zone (FAZ) area in the study group after nicotine gum intake.
The primary aim of this study was to investigate the early effects of chewing nicotine gum on retinal microcirculation. Macular microcirculation, evaluated according to SCP area, DCP area, CC flow area, and FAZ area parameters, was significantly lower in the study group than controls at 1 hour after gum chewing.
The absorption of nicotine from gum is slower and the increase in nicotine blood levels is more gradual than with smoking. The bioavailability of nicotine in gum form is lower than in smoking due to first-pass metabolism and the fact that some nicotine is retained in the gum.17 Based on these pharmacokinetic properties of nicotine, we measured choroidal thickness 1 hour after consumption.18
This study reveals that the acute effects of nicotine disrupt macular microcirculation. In addition, for the first time it was possible to individually measure retinal vessel density in the superficial and deep retinal layers with OCTA, which revealed decreased vessel density in both the superficial and deep retinal layers in all quadrants 1 hour after nicotine gum use. No significant change in blood flow or vessel density was observed in the deep or superficial retinal layer in the placebo group.
Smokers take in more than 600 toxic agents, primarily nicotine.19 Retinal perfusion, especially in the macular area, is a significant indicator of ocular perfusion and is crucial for normal vision.20 The retinal vasculature is affected by many local and systemic factors.20–25 Variations in these factors can result in damage to retinal vascular structures and visual deterioration due to macular damage.26 Rojanapongpun et al.5 studied the effect of nicotine on ophthalmic artery flow velocity using transcranial Doppler ultrasound. They observed that small doses of nicotine caused an increase in blood flow velocity in the ophthalmic artery and a decrease in digital blood flow in the nicotine-exposed glaucoma group. Steigerwalt et al.27 found a reduction in blood flow velocity in the posterior ciliary artery after smoking. Shoshani et al.28 demonstrated significant correlation between ocular perfusion pressure (OPP) and central retinal artery peak systolic pressure, especially in diabetic primary open-angle glaucoma patients who had been evaluated with color Doppler imaging. We did not observe any significant difference in systolic/diastolic blood pressure or IOP after nicotine gum administration. Assuming that OPP did not change significantly either, the effect exerted by nicotine could be related to increased local factors such as plasma vasopressin or angiotensin 2, epinephrine, and norepinephrine levels, as described in previous studies.29,30
The literature includes conflicting data concerning ocular perfusion in habitual smokers. Morgado et al.4 reported that smoking in habitual smokers caused no significant change in retinal blood velocity through large vessels and a significant vasoconstriction in the retinal vessel, resulting in a 10% decrease in retinal blood flow rate. In contrast, Tamaki et al.31 and Robinson et al.32 reported that smoking resulted in increases in ocular blood flow and perfusion in habitual smokers. The latter studies are contradictory to our findings; however, our study was conducted in healthy non-smokers. A possible explanation for this is that the effect of smoking and nicotine on tissue circulation may be different between non-smokers, light smokers, and chronic smokers.33–37 Also, El-Shazly et al.38 showed that CFT, SFCT, and multifocal electroretinography (mfERG) ring ratios were significantly lower in active smokers compared to passive smokers. Tamaki et al.39 reported decreases in optic nerve head, macular, and choroidal perfusion measured by laser speckle method 30 minutes after smoking in light smokers. However, they assessed ocular blood flow using an indirect method based on measuring vessel diameter, whereas we measured it directly as flow area on OCTA.
Discrepancies in the literature regarding macular and optic nerve head perfusion may be related to differences in tissue response to nicotine in habitual and light or non-smokers. The effects of smoking on vascular tissues may vary in the acute and chronic periods. There are studies reporting an initial decrease in choroidal thickness, which was attributed to decreased blood flow to the choroid in the early period, followed by an increase in choroidal thickness hours after smoking, which was hypothesized to result from congestion of the choroid due to inflammation or hypoxia.40 Other studies have reported that smoking causes acute hemodynamic and vascular changes, and chronic smoking leads to vascular dysfunction in the eye.41,42 Nicotine causes peripheral vasoconstriction and increases peripheral vascular resistance. Furthermore, smoking increases carbon monoxide levels, thereby reducing oxygen transport to the tissues and causing downstream vasodilatation and increased blood flow velocity.43 A study by Campisi et al.44 demonstrated that chronic smoking is associated with reduced endothelium-dependent vasodilatation, regardless of the presence of other vascular pathologies such as atherosclerosis.
Individual variations in choroidal thickness have been reported in relation to age, refractive error, AL, and diurnal rhythm.45–47 In our study, there was no statistically significant difference between the groups with regard to these parameters. In addition, we performed all measurements during morning hours to avoid diurnal fluctuations. Besides macular microcirculation, choroidal blood flow was also measured in our study. Zengin et al.18 evaluated the acute effect of chewing nicotine gum on choroidal thickness in non-smokers with spectral-domain OCT and reported a significant decrease in choroidal thickness. Similarly, a study by Sızmaz et al.48 demonstrated significant reduction in choroidal thickness 1 hour after smoking in habitual smokers.
Nicotine causes cholinergic effects, typically by binding acetyl choline receptors. Nicotine receptors are present in many tissues including the eye, where they are found mostly in the choroidal plexus, inner plexiform layer, and capillary endothelium.49,50 Therefore, the acute receptor-mediated effects of nicotine are expected to manifest primarily in the choroid, capillary bed, and inner plexiform layer. The decreases in choroidal flow, choroidal thickness, and vascular flow throughout the retinal vasculature (superficial and deep) demonstrated in our study may confirm the receptor-mediated effect of nicotine. However, we were unable to detect any significant changes in the inner plexiform layer of the retina, unlike the study by Varghese et al.51 that showed deterioration of the inner plexiform layer in mfERG measurements after chewing 2-mg and 4-mg nicotine gum.
The lack of nicotine blood level measurements in our subjects is a limitation of our study. However, Russell et al.52 reported that maximum blood plasma nicotine level was obtained 1 hour after chewing 4-mg nicotine gum. Additionally, lack of peripheral carboxyhemoglobin blood levels, arterial blood analysis, and mfERG measurements to evaluate functional response of the retina are other limitations of our study.
OCTA, as a new and non-invasive technique, enables automatically measurements (except choroidal thickness) and reduces error associated with manual measurement. This study is the first in the literature to demonstrate the effect of nicotine on superficial and deep retinal layers using OCTA. Automatic measurement of choroidal flow as CC flow area by OCTA is an advantage of our study over previous studies that estimated this parameter using manual measurements of choroidal thickness on spectral-domain OCT images.
To the best of our knowledge, this is the first study to investigate the isolated effects of nicotine on macular microcirculation using OCTA. As there is growing evidence in the literature about the relationship between macular microcirculation and ocular or choroidal blood flow, the findings of this preliminary study may be of clinical importance. We believe that the results of this study will be useful in future research on this topic.