Impact of excess light and yellow filters on accumulation of lipofuscin … · 2017. 1. 5. ·...

Pacific UniversityCommonKnowledge

Faculty Scholarship (COO) College of Optometry

Fall 10-24-2014

Impact of excess light and yellow filters onaccumulation of lipofuscinJohn R. HayesPacific University

David K. GlabePacific University

Follow this and additional works at: http://commons.pacificu.edu/coofac

Part of the Optometry Commons

This Article is brought to you for free and open access by the College of Optometry at CommonKnowledge. It has been accepted for inclusion inFaculty Scholarship (COO) by an authorized administrator of CommonKnowledge. For more information, please [email protected].

Recommended CitationHayes, John R. and Glabe, David K., "Impact of excess light and yellow filters on accumulation of lipofuscin" (2014). FacultyScholarship (COO). Paper 30.http://commons.pacificu.edu/coofac/30

http://commons.pacificu.edu?utm_source=commons.pacificu.edu%2Fcoofac%2F30&utm_medium=PDF&utm_campaign=PDFCoverPages

http://commons.pacificu.edu/coofac?utm_source=commons.pacificu.edu%2Fcoofac%2F30&utm_medium=PDF&utm_campaign=PDFCoverPages

http://commons.pacificu.edu/coo?utm_source=commons.pacificu.edu%2Fcoofac%2F30&utm_medium=PDF&utm_campaign=PDFCoverPages

http://commons.pacificu.edu/coofac?utm_source=commons.pacificu.edu%2Fcoofac%2F30&utm_medium=PDF&utm_campaign=PDFCoverPages

http://network.bepress.com/hgg/discipline/730?utm_source=commons.pacificu.edu%2Fcoofac%2F30&utm_medium=PDF&utm_campaign=PDFCoverPages

http://commons.pacificu.edu/coofac/30?utm_source=commons.pacificu.edu%2Fcoofac%2F30&utm_medium=PDF&utm_campaign=PDFCoverPages

mailto:[email protected]

Impact of excess light and yellow filters on accumulation of lipofuscin

DescriptionPurpose. Previous reports suggest excess high energy, short wave light increase lipofuscin fluorophoreaccumulation in the retinal pigment epithelium layer. Oxidation of lipofuscin has been implicated in thegenesis of macular degeneration. By taking advantage of the increased exposure to light by optometrystudents, we tested whether optometry students accumulate more lipofuscin fluorophores than similarly agedallied health students and whether yellow filters alter lipofuscin accumulation.

Method. The sample consisted of 54 non-optometry students (Mean age27, 4.1SD; 63% Female), 62 first-yearoptometry students (Mean age 27, 4.9SD; 55% female), and 39 second-year students (Mean age 26, 3.8SD,54% female). First year practice patients were exposed primarily to anterior segment biomicroscopy, whilesecond year practice patients included posterior segment biomicroscopy with condensing lens and binocularindirect ophthalmoscopy sessions. A two distribution mixture model estimated the gray scale of thefluorescent lipofuscin ring around the macula.

Results. There was significantly less luminance intensity in optometry students (Mean 70.8 grayscale) relativeto non-optometry students (Mean 76.2 grayscale, F = 5.3, p=.024) which was opposite from our prediction.Covariates included ge (b=.9,p=.002) and baseline lipofuscin (b=1.1, p

Conclusion. Our results were more consistent with oxidation of lipofuscin fluorophores than accumulationfollowing the excess exposure to light as practice patients. The study revealed intriguing trends in a challengingenvironment that suggested the topic is worth further investigation in a more rigorous experimentalenvironment. The bottom line however is that we do not trust our results over time due to the systematiceffect of multiple camera flashes that were not controlled across patients. We sincerely believe this study needsreplicated with an autofluorescence camera that has a reference point to adjust for the physical conditions.

KeywordsLipofuscin; blue light; yellow filters; fundus autofluorescence; A2E

DisciplinesOptometry

CommentsThis original research manuscript has not undergone peer review.

RightsTerms of use for work posted in CommonKnowledge.

This article is available at CommonKnowledge: http://commons.pacificu.edu/coofac/30

http://commons.pacificu.edu/rights.html

http://commons.pacificu.edu/coofac/30?utm_source=commons.pacificu.edu%2Fcoofac%2F30&utm_medium=PDF&utm_campaign=PDFCoverPages

Impact of excess light and yellow filters on accumulation of lipofuscin

John R. Hayes Ph.D.

Pacific University Oregon

David K. Glabe OD MS

Pacific University Oregon

Correspondence:

John R. Hayes

College of Optometry

Pacific University

2043 College Way

Forest Grove, Oregon

Fax: 503 352 2929

Email: [email protected]

Acknowledgement:

The study was funded by the Macular Degeneration Foundation, Las Vegas, NV

Contact lenses were supplied by CooperVision

Lipofuscin is a complex aggregate of indigestible lysosomal material which accumulates in postmitotic

cells over the lifetime of an individual.1 While lipofuscin has been considered a biological marker for the

aging of cells, abnormally high levels of lipofuscin within the retinal pigment epithelium (RPE) are

associated with retinal disease and RPE dysfunction, as in Stargardt’s and age-related macular

degeneration.2, 3 Laboratory evidence suggests4 that RPE lipofuscin pigments are unique from that of

other cells as they are derived from molecular components of the visual cycle and primarily form during

periods of excess light exposure with significant rhodopsin bleaching and elevated levels of all-trans-

retinal in the rod outer segment (ROS) disks.5-7 Under these circumstances, the rate of generation of all-

trans-retinal by photo-activation of rhodopsin exceeds the rate at which all-trans-retinal is reduced to

all-trans-retinol in the ROS, providing a substrate for random side reactions to the visual cycle. Various

fluorescent byproducts of the visual cycle are major components of RPE lipofuscin, including the di-

retinal conjugate A2E (N-retinylidene-N-retinylethanolamine), which can induce DNA damage and RPE

cell apoptosis through photooxidative processes upon exposure to short-wavelength (blue) light.8-10

These lipofuscin fluorophores have been shown to sensitize the RPE to blue light damage and are

thought to play a role in the pathogenesis of certain macular diseases.11-13 It has been proposed that A2E

and other lipofuscin fluorophores may be quantified via in vivo fundus autofluorescence imaging14.

Quantification of these molecules and methods of altering their accumulation may be of clinical interest

in assessing and altering risk of various maculopathies.15

Optometry students have unusual exposure to high levels of light as they serve as practice

patients for their colleagues in learning various ophthalmoscopic examination procedures over a four-

year period of professional education. Our first study objective was to determine if excess light

exposure in optometry students relative to non-optometry health profession students leads to greater

accumulation of lipofuscin fluorophores.

Many ophthalmic instruments utilize light sources weighted toward shorter wavelengths more likely to

result in photo-oxidation of lipofuscin fluorophores such as A2E. The resulting products of lipofuscin

fluorophores may show increased fluorescence with early photo-oxidation;14 further oxidation and

photodegradation, however, may cause a decrease in autofluorescence above 540 nm.1, 16-20 Our second

study objective was to determine if blue light-blocking yellow filters would alter lipofuscin fluorophore

accumulation (as measured by fundus autofluorescence imaging) by having optometry students wear a

yellow contact lens on one randomly assigned eye during procedure practice sessions.

Method. This was a prospective cohort study for the comparison of fundus autofluorescence measures

of lipofuscin fluorophores in optometry and non-optometry students and a randomized controlled trial

exploring the effect of yellow filters on lipofuscin fluorophore accumulation within optometry students.

The research followed the tenets of the Declaration of Helsinki and informed consent was obtained from

subjects after explanation of the nature and possible consequences of the study. The study was

approved by the Pacific University Institutional Review Board.

Subjects. We recruited 61 first-year non-optometry students from the Pacific University College of

Health Professions who are in a three-year program, 62 first-year optometry students from the class of

2013 and 38 second-year students from the class of 2012. Participation was voluntary. Optometry

students were paid $10 per session and non-optometry students were paid $30 per session. The pay

differential was due to the requirement that non-optometry students had to drive from a different

campus (7 miles). Optometry students were also paid $90 for maintaining a practice log. The primary

outcome variable was digital luminance levels of serial fundus autofluorescence photographs. The study

was powered to detect a 0.5SD mean difference in luminance between optometry and non-optometry

students with a power of .9 at an alpha = .05 assuming a correlation between the baseline luminance

covariate and the follow-up of r = 0.7 with a 20% dropout.

Subjects had to have two healthy, normally functioning eyes. Those who reported any history of

eye disease or hereditary eye conditions were excluded. Individuals with visual correction were allowed

but must otherwise have had healthy functioning eyes. Optometry subjects had to be able to tolerate

contact lens wear, but were not required to be previous contact lens wearers. Biomicroscopy was

performed prior to administering mydriatic eye drops as typically done in routine eye examination to

assess risk of acute angle closure. Non-optometry subjects must have had von Herrick Grade 2 or larger

anterior chamber angles to ensure safety with dilation. Pregnant subjects were excluded (two non-

optometry students became pregnant during the study and were excluded from further participation

due to possible side effects of dilation).

Equipment and materials. A Topcon TRC-50DX retinal camera (Topcon, Tokyo) was used to collect data

from control and optometry subjects. The camera employs an excitation filter that produces a green

flash from 535nm to 595nm and a barrier filter for collection of flourescent light from 600nm to 730nm.

The camera was located in a completely dark room, and lights on the control panel were covered when

taking photographs to exclude any light other than the excitation flash.

CooperVision (Pleasanton, CA) supplied Edge III ProActive contact lenses (62% polymacon and

36% water) which were tinted yellow by SpecialtyTint (Escondido, CA). Subjects used the same lens

throughout the trial and were supplied with identical contact lens cleaner and cases. The contact lenses

exhibited the spectral profile of a longpass filter with cutoff at 470nm (above the 430 nm point of

oxidation for A2E). Contact lenses were removed prior to fundus imaging.

Optometry subjects completed a log sheet each time they served as a patient for practicing

ophthalmic procedures. Logs included the duration of light exposure to each eye and type of

ophthalmic equipment used (e.g. biomicroscope with or without condensing lens, binocular indirect

ophthalmoscopy). The file was monitored weekly for adherence to completion.

Procedure. Baseline fundus autofluorescence photographs were collected in January 2010 and follow-

up data in September 2010, yielding a nine month period of accumulation. Very little practice occurred

over the summer from June through August.

Subjects were recruited by a general email sent to first and second-year optometry students and first-

year professional students in all Pacific University’s College of Health Profession programs. Subjects

completed a brief questionnaire that included gender, age, ethnicity, refractive correction, and

nutritional supplementation.

Baseline photographs were taken by two photographers (optometry student research

assistants). Photographers alternated taking the first baseline photograph. Immediately following that

photograph the other photographer took a second photograph. For each photograph the camera was

refocused. Two photographs were also taken at follow-up but by the same photographer. The initial

baseline photographs were taken at flash intensity 50 watt seconds, but follow-up photographs were at

flash intensity 100 watt seconds. We chose the initial intensity for subject comfort, but concluded that a

higher intensity facilitated autofluorescence detection. The maximum for the camera was 350 watt

seconds Changing intensity prohibited direct measures of change from baseline; instead, baseline

measures were used as covariates to adjust for individual differences. Subsequent analysis

demonstrated that our method of computing luminance was accurate at either level of flash intensity.

Non-optometry students had their photographs taken on weekends and in the evening.

Optometry students had photographs scheduled at times during which they would be dilated for

practice or lab sessions, with images being acquired prior to light exposure as a practice patient. Eyes

were not bleached prior to the test photograph. Subject pupils were dilated at least 8 mm in diameter

before image acquisition as measured by a ruler prior to the photograph.

For optometry students, the yellow contact lens was randomized to either the left or right eye

at study entry and the same eye was filtered for the entire study. Optometry students wore the yellow

contact lens when exposed to light as a practice patient except for limited procedures requiring direct

contact of ophthalmic equipment to the cornea. During direct contact procedures, students utilized

yellow filters built into biomicroscopes when the eye randomized to the yellow lens was examined. If

biomicroscope filters were not available, then the student proceeded without filtering light.

Luminance calculation. The primary outcome measure was luminance intensity of the Topcon

autofluorescence photograph. The grayscale varied from black (0) to white (255). Figure 1a is a sample

autofluorescence photograph. A mixture model was developed using R (GNU, Free Software

Foundation). Figure 1b is the frequency distribution of the pixels along the grayscale and the gamma

distribution model of the distributions. The R function reading the TIFF files had automatic brightness

adjustment, so a small white square (10x10 pixel grayscale 255) was added to a black corner (grayscale

0) of each photograph in order to calibrate all pictures to the same brightness scale. The top one

percent of the brightness pixels and pixels less than a grayscale of four were eliminated from the

distribution to remove the black corners of the photograph and the extreme upper tail of brightness.

Our goal was to estimate the overall luminance of the brighter perifoveal ring of autofluorescence. The

smooth lines in Figure 1b show two modal points. The left distribution represents the distribution of

points primarily making up the pixels from the optic disc, macula, and main vessels. The right

distribution is the bulk of the lighter vessels and the gray of the entire photograph. We had two

research assistants independently use the open source graphics program GIMP to identify pixels that

best represented the “hyperfluorescent ring” around the macula. They used the Threshold function

within GIMP which sets all points black below a particular threshold and white above. Figure 1c is the

threshold view of Figure 1a. The small inset histogram identifies the threshold at grayscale 58 which

was approximately the mean of the higher distribution in Figure 1b. The researchers consistently chose

a point near the mean of the upper mixture distribution. This point best defined the bright ring around

the maculaFigure 1d shows the consistency in judgment (reliability) between the two research assistants

in estimating the mean autofluorescence luminance. In this figure, data are also shown on judgments

for major vessels. Two consecutive photographs were taken on each subject at baseline and follow-up.

Photograph 1 and 2 were significantly associated for both research assistant judge 1 (b=1.4, R2 = .92,

p<.001) and judge 2 (b=1.01, R2 = .90, p<.001) further supporting the reliability of the measure. Using

the subjective estimates as a guide for defining a rule for the computer, we averaged the pixel grayscale

above the mixture model mean of the second distribution as the estimate of the luminance of

autofluorescence.

The validity of our measure was calculated in several ways. There was a significant association

between baseline and follow-up measurements (R2 = 0.76, p<.001) demonstrating baseline measures

could predict luminance 9 months later. Age was significantly associated with baseline mean luminance

(R2 = 0.16, p<.001) as would be expected since lipofuscin accumulates over time. In testing the Topcon

camera on a blank piece of paper with the words “Can you see me now?”, we noted that the measured

luminance linearly increased with serial pictures every 10 seconds over a period of 40 trials (slope = .42

gray scale, R2 = .95, p<.001). We could see the text because the copy paper we used had added

fluorescence to make it brighter. The increase in luminance over time was likely due to heating of the

camera flash bulb. Considering the consecutive photographs taken during the study, the overall

baseline mean luminance was 45.50 gray scale for the first photograph and 45.91 for the second

photograph, a difference of .41. This compared favorably to the mean 10 second difference for plain

copy paper of .42 (copy paper autofluoresces due to fluorescent material added to the paper during

manufacturing).

Statistics. A between subjects analysis of covariance with baseline luminance and age covariates

assessed the first hypothesis of whether or not there was a difference between lipofuscin fluorophore

accumulation in optometry and non-optometry students as measured by fundus autofluorescence.21 A

within subjects analysis of covariance with baseline luminance and age covariates assessed the effect of

yellow filters on follow-up luminance. Figures are presented with 84% confidence intervals. These

confidence intervals mimic the results from unadjusted least significant difference tests at an p<.05.

Figure 1. Calculating luminance

Results.

Sample: Demographics of the sample are in Table 1.

student because of dropping out of school and

others due to an inability to locate.

57 (92%) first year students, 38 (97%) second year students, and 53(98%) of non

photographs were lost due to subjects dropping out of the study. Those remaining were 41 (72%) first

years, 34 (89%) second years, and 33 (62%) non

luminance at baseline for first year optometry students (45.4, 12.3SD versus 37.9, 13.8SD, t=2.93

p=.004). Second year and non-optometry dropouts tended to have higher baseline luminance means

but the differences were not statistically

versus 43.9, 16.2SD for second year and non

Demographics of the sample are in Table 1. At the outset of the study we lost 1 second year

student because of dropping out of school and two non-optometry students due to pregnancy and 5

others due to an inability to locate. Photographs of sufficient quality to be processed were available for

8 (97%) second year students, and 53(98%) of non-optometry. Follow


33 (62%) non-optometry students. Dropouts had significantly higher


optometry dropouts tended to have higher baseline luminance means

but the differences were not statistically significant (49.9, 15.6SD versus 43.3, 12.3SD and 51.2, 20.1SD

versus 43.9, 16.2SD for second year and non-optometry respectively).

e lost 1 second year

pregnancy and 5

Photographs of sufficient quality to be processed were available for

optometry. Follow-up


gnificantly higher


optometry dropouts tended to have higher baseline luminance means

significant (49.9, 15.6SD versus 43.3, 12.3SD and 51.2, 20.1SD

Table 1. Sample demographics at baseline.

First Years

(n=61)

Second Years

( n=39)

Non-Opt

(n=62)

Mean / % (SD) Mean / % (SD) Mean / % (SD)

Age (yrs) 27.3 (4.9) 26.5 (3.8) 26.8 (94.1)

Women (%) 54.8 53.8 63.0

Caucasian (%) 82.3 79.5 70.4

Asian (%) 17.7 15.4 24.1

Other (%) 5.1 5.6

Wore Correction (%) 72.6 64.1 44.4

Correct w/ contacts (%) 67.7 76.9 18.5

Slit-Lamp (minutes) 131.3 (71.6) 21.0 (24.1)

LED BIO (minutes) 1.4 (5.0) 14.9 (20.7)

Non-LED BIO (minutes) 0.7 (2.4) 142.1 (101.3)

High Plus (minutes) 13.5 (14.6) 141.6 (99.2)

Retinoscope (minutes) 34.1 (31.8) 2.2 (5.3)

Ophthalmoscope (minutes) 20.2 (22.3) 0.5 (2.0)

Other Exposure (minutes) 13.8 (4.4) 43.7 (11.6)

Total Exposure (minutes) 215.0 (106.9) 366.0 (183.8)

Hypothesis 1: Lipofuscin autofluorescence increases in optometry students as a function of

increased light exposure over non-optometry student controls (Figure 2). A between subject analysis of

covariance revealed significantly less luminance intensity (implied less lipofuscin) in optometry students

(Mean 70.8 grayscale) relative to non-optometry students (Mean 76.2 grayscale, F = 5.3, p=.024) which

was the opposite from our hypothesis. The effect size for this difference was -.52SD (DifferenceOpt-

NonOpt/SD = -5.4/10.5). The covariate influence on follow-up luminance in the model were age (b= .9

grayscale/age year, t=3.2, p=.002), baseline luminance (b=1.1 grayscale, t=15.1, p<.001), and replicate

photograph (b=1.7 grayscale for second photograph, t=2.2, p=.03). Figure 2 illustrates the adjusted

grayscale means for optometry and non-optometry students at nine month follow-up. Visual inspection

revealed no observable evidence of RPE damage in the follow-up autofluorescence photographs of

either group of students.

Table 2. Hypothesis 1: Model mean comparisons at follow-up luminance as a function of starting

baseline. Least significant t-test of optometry versus non-optometry students (Means square error =

99.6, 107df). Effect size is the difference between means divided by the root mean square error.

General linear model: Follow-up = 18.95 – 8.0(1st year) – 21.7 (2nd year) + 1.39 (Baseline) +

0.09(1st yr * Baseline) + 0.42 (2nd year * Baseline)

Group Quartile Baseline Follow-up

Difference

from Non-

Opt

t p Effect

Size (SD)

First Year Minimum 9.8 25.4 -7.1 -3.55 0.001 -0.71

25 32.1 58.3 -5.1 -2.55 0.012 -0.51

50 42.9 74.3 -4.1 -2.06 0.041 -0.41

75 51.3 86.7 -3.4 -1.69 0.095 -0.34

Maximum 91.2 145.6 0.2 0.11 0.914 0.02

Second Year Minimum 9.8 14.9 -17.6 -8.78 0.000 -1.76

25 32.1 55.3 -8.1 -4.06 0.000 -0.82

50 42.9 74.8 -3.6 -1.78 0.077 -0.36

75 51.3 90.0 0.0 -0.01 0.996 0.00

Maximum 91.2 162.2 16.9 8.42 0.000 1.69

Non-Optometry Minimum 9.8 32.5

25 32.1 63.4

50 42.9 78.4

75 51.3 90.1

Maximum 91.2 145.3

Figure 2. Luminance accumulation over 9 months

Hypothesis 2: Yellow filters will alter the

no effect of yellow filter for the first

filtered, t=.938/1.5, p=.532). The effect size for the sec

1.97/7.58), which was not statistically significant (mean = 72.0 unfiltered and 74.0 filtered, t = 1.5 , p=

.14). Age (b=.99, F=11.6, p=.001) and baseline luminance (b=1.34, F=309.5, p<.001) were significant

covariates, but replicate photograph (1.5 gray scale units greater on the second photo, F= 2.6, p=.11) did

not reach statistical significance.

After controlling for age and baseline luminance, there was no dose effect of total light exposure

follow-up luminance (p=.95). There was significantly more

class (Mean 366 minutes) than in the first year

exposure difference between filter and no filter (p= .574) or the group by filter interaction (p=.365).

. Luminance accumulation over 9 months

will alter the accumulation of lipofuscin fluorophores (Figure 3)

filter for the first-year class of optometry students (mean 69.4 unfiltered and 68.5

filtered, t=.938/1.5, p=.532). The effect size for the second-year optometry students was .26SD (


6, p=.001) and baseline luminance (b=1.34, F=309.5, p<.001) were significant


line luminance, there was no dose effect of total light exposure

up luminance (p=.95). There was significantly more practice light exposure in the second year

than in the first year (Mean 215 minutes, p<.001). However t


(Figure 3). There was

69.4 unfiltered and 68.5

year optometry students was .26SD (-


6, p=.001) and baseline luminance (b=1.34, F=309.5, p<.001) were significant


line luminance, there was no dose effect of total light exposure on

exposure in the second year

. However there was no


Figure 3. Yellow filters v unfiltered

Discussion.

Prior research has demonstrated that light exposure results in the accumulation of RPE

lipofuscin fluorophores. We hypothesized that optometry students’ exposure to excess light while

serving as practice patients would lead to more lipofuscin

baseline autofluorescence luminance (lipofuscin proxy), optometry students had significantly less

accumulation at nine months follow

difference.

While most previous research has supported the concept of increased lipofuscin with

light exposure, Morgan et al have shown a reduction in autofluorescence in

macaques after light exposure at 568 nm.

levels of light exposure. Subsequent analysis suggests that the processes of photoisomerization,

photooxidation and photodegradation may explain this phenomenon.

of light exposure led to permanent RPE cell dysfunction as viewed with an adaptive optics scanning laser

ophthalmoscope (AOSLO). We noted a decline in

not detect damage to RPE cells, although we lacked an AOSLO.

The second hypothesis tested whether yellow filters could alter lipofuscin accumulation. We

found no scientifically relevant trend of filter for first years, effect size equal to .12SD. However, we



serving as practice patients would lead to more lipofuscin autofluorescence. After adjusting for age and

luminance (lipofuscin proxy), optometry students had significantly less

accumulation at nine months follow-up. The effect was a scientifically meaningful .5 standard deviation

le most previous research has supported the concept of increased lipofuscin with

light exposure, Morgan et al have shown a reduction in autofluorescence in

macaques after light exposure at 568 nm.18 They found transient decreases in autofluorescence


photooxidation and photodegradation may explain this phenomenon. In Morgan's study, higher levels

exposure led to permanent RPE cell dysfunction as viewed with an adaptive optics scanning laser

ophthalmoscope (AOSLO). We noted a decline in autofluorescence in our optometry students but did

not detect damage to RPE cells, although we lacked an AOSLO.





. After adjusting for age and

luminance (lipofuscin proxy), optometry students had significantly less

up. The effect was a scientifically meaningful .5 standard deviation

le most previous research has supported the concept of increased lipofuscin with increased

ound transient decreases in autofluorescence at low


In Morgan's study, higher levels

exposure led to permanent RPE cell dysfunction as viewed with an adaptive optics scanning laser

autofluorescence in our optometry students but did



noted a small trend for second year students (.26SD) which was not significant. We could not rule out

chance as a reasonable alternative to the differences found.

One possible explanation for our findings is that excess light exposure led to increased oxidation

and photodegradation of lipofuscin fluorophores such as A2E within eyes of optometry students relative

to non-optometry students. Oxidation of lipofuscin fluorophores decreases fluorescence above 540nm

(our study camera’s barrier filter collects fluorescent light from 615-715nm). Oxidation of lipofuscin

occurs more readily at short wavelengths, and thus may have been reduced by the presence of a yellow

filter, as has previously been demonstrated to occur in vitro. Light exposure in second-year optometry

students was greater as they were exposed to procedures involving more direct illumination of the

fundus (high plus and biomicroscopy (BIO)), while first years were exposed primarily to anterior segment

BIO. This may explain why the protective effect of yellow filters was present only in second-year

optometry students. The filter effects were trends only and were not significantly different.

We acknowledge a number of limitations to our study which should provoke a cautious

interpretation of results. While we were confident in our ability to quantify autofluorescence with the

Topcon camera, the device was not designed for this purpose. The quantification method of analysis

was by computer program and there was no subjective component. The difference between

consecutive photographs was detectable and similar to the difference between consecutive

photographs of plain copy paper with added fluorescence caused by the heating of the instrument’s

flash bulb.

We lost access to our Topcon camera after nine months, at which point a Heidelberg Spectralis

with BluePeak SLO/OCT (Heidelberg, Carlsbad, CA) was acquired and utilized in following the subjects for

another year. The Spectralis was also not designed to quantify lipofuscin. The Spectralis proved more

difficult for our photographers to operate, and blue light laser exposure time was variable for the

subject as the instrument required multiple photographs of a certain quality. The Spectralis could not

be run in a dark room, allowing uncontrolled ambient light during photography. We were not able to

demonstrate reliability or validity for quantifying luminance with the Spectralis in any of the

measurements described above for the Topcon camera. Subsequent analysis showed no correlation

between the Topcon baseline and Spectralis follow-up, or even an appreciable correlation between first

and second consecutive photographs within a Spectralis imaging session. There was no correlation with

age. A reliable and valid method of quantifying lipofuscin has been more recently designed for the

Spectralis, but the new modification of the camera was unavailable to us at the time of our study.14, 22

The study suffered from attrition. For many of the first year optometry students, managing a practice

log and using the contact lens was too much of a distraction to continue in the study. The non-

optometry students were from a different campus in a different town and the inconvenience of the trip

may have contributed to a number of subjects choosing not to participate in the follow-up visit. Future

studies will need to consider ways to reduce these barriers to study completion.

We recognize that talking about non-significant trends is hazardous. This study should be

replicated once a reliable and validated measure of quantifying autofluorescence is available. Our

student population appeared to be a reasonable working sample for this type of study; however, the age

and health of this study population may limit application of results to older patients more at risk for

retinal disease. Replication of these findings has important clinical implications for understanding the

role of light exposure in lipofuscin fluorophore measures and its possible relation to retinal disease.

References

1. Sparrow JR, Gregory-Roberts E, Yamamoto K, Blonska A, Ghosh SK, Ueda K, Zhou J. The bisretinoids of

retinal pigment epithelium. Prog Retin Eye Res Mar 2012;31(2):121-35. Available from:

http://sfxhosted.exlibrisgroup.com/pacificu?sid=OVID:medline&id=pmid:22209824&id=doi:10.1016%2F

j.preteyeres.2011.12.001&issn=1350-9462&isbn=&volume=31&issue=2&spage=121&pages=121-

35&date=2012&title=Progress+in+Retinal+%26+Eye+Research&atitle=The+bisretinoids+of+retinal+pigm

ent+epithelium.&aulast=Sparrow&pid=%3Cauthor%3ESparrow+JR%3BGregory-

Roberts+E%3BYamamoto+K%3BBlonska+A%3BGhosh+SK%3BUeda+K%3BZhou+J%3C%2Fauthor%3E%3C

AN%3E22209824%3C%2FAN%3E%3CDT%3EJournal+Article%3C%2FDT%3E. Accessed 20120220.

2. Sparrow JR, Fishkin N, Zhou J, Cai B, Jang YP, Krane S, Itagaki Y, Nakanishi K. A2E, a byproduct of the

visual cycle. Vision Res Dec 2003;43(28):2983-90.

3. Delori FC, Staurenghi G, Arend O, Dorey CK, Goger DG, Weiter JJ. In vivo measurement of lipofuscin in

stargardt's disease--fundus flavimaculatus. Invest Ophthalmol Vis Sci Oct 1995;36(11):2327-31.

4. Wolf G. Lipofuscin and macular degeneration. Nutr Rev Oct 2003;61(10):342-6.

5. Ben-Shabat S, Parish CA, Vollmer HR, Itagaki Y, Fishkin N, Nakanishi K, Sparrow JR. Biosynthetic studies

of A2E, a major fluorophore of retinal pigment epithelial lipofuscin. J Biol Chem Mar 1 2002;277(9):7183-

90. Available from:

http://sfxhosted.exlibrisgroup.com/pacificu?sid=OVID:medline&id=pmid:11756445&id=doi:&issn=0021-

9258&isbn=&volume=277&issue=9&spage=7183&pages=7183-

90&date=2002&title=Journal+of+Biological+Chemistry&atitle=Biosynthetic+studies+of+A2E%2C+a+majo

r+fluorophore+of+retinal+pigment+epithelial+lipofuscin.&aulast=Ben-Shabat&pid=%3Cauthor%3EBen-

Shabat+S%3BParish+CA%3BVollmer+HR%3BItagaki+Y%3BFishkin+N%3BNakanishi+K%3BSparrow+JR%3C

%2Fauthor%3E%3CAN%3E11756445%3C%2FAN%3E%3CDT%3EJournal+Article%3C%2FDT%3E. Accessed

20020225.

6. Katz ML, Drea CM, Eldred GE, Hess HH, Robison WG,Jr. Influence of early photoreceptor degeneration

on lipofuscin in the retinal pigment epithelium. Exp Eye Res Oct 1986;43(4):561-73.

7. Sparrow JR, Vollmer-Snarr HR, Zhou J, Jang YP, Jockusch S, Itagaki Y, Nakanishi K. A2E-epoxides

damage DNA in retinal pigment epithelial cells. vitamin E and other antioxidants inhibit A2E-epoxide

formation. J Biol Chem May 16 2003;278(20):18207-13.

8. Zhou J, Kim SR, Westlund BS, Sparrow JR. Complement activation by bisretinoid constituents of RPE

lipofuscin. Invest Ophthalmol Vis Sci Mar 2009;50(3):1392-9. Available from:

http://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&D=medl&AN=19029031;

http://sfxhosted.exlibrisgroup.com/pacificu?sid=OVID:medline&id=pmid:19029031&id=doi:&issn=0146-


9&date=2009&title=Investigative+Ophthalmology+%26+Visual+Science&atitle=Complement+activation

+by+bisretinoid+constituents+of+RPE+lipofuscin.&aulast=Zhou&pid=%3Cauthor%3EZhou+J%3BKim+SR

%3BWestlund+BS%3BSparrow+JR%3C%2Fauthor%3E%3CAN%3E19029031%3C%2FAN%3E%3CDT%3EJo

urnal+Article%3C%2FDT%3E.

9. Schutt F, Bergmann M, Holz FG, Dithmar S, Volcker HE, Kopitz J. Accumulation of A2-E in

mitochondrial membranes of cultured RPE cells. Graefes Arch Clin Exp Ophthalmol Mar

2007;245(3):391-8.

10. Sparrow JR, Nakanishi K, Parish CA. The lipofuscin fluorophore A2E mediates blue light-induced

damage to retinal pigmented epithelial cells. Invest Ophthalmol Vis Sci Jun 2000;41(7):1981-9.

11. Schutt F, Davies S, Kopitz J, Holz FG, Boulton ME. Photodamage to human RPE cells by A2-E, a

retinoid component of lipofuscin. Invest Ophthalmol Vis Sci Jul 2000;41(8):2303-8.

12. Sparrow JR, Zhou J, Ben-Shabat S, Vollmer H, Itagaki Y, Nakanishi K. Involvement of oxidative

mechanisms in blue-light-induced damage to A2E-laden RPE. Invest Ophthalmol Vis Sci Apr

2002;43(4):1222-7.

13. Delori F, Greenberg JP, Woods RL, Fischer J, Duncker T, Sparrow J, Smith RT. Quantitative

measurements of autofluorescence with the scanning laser ophthalmoscope. Invest Ophthalmol Vis Sci

2011;52(13):9379-90. Available from: http://alliance-

primo.hosted.exlibrisgroup.com/openurl/PU/pu_services_page?sid=OVID:medline&id=pmid:22016060

&id=doi:10.1167%2Fiovs.11-8319&issn=0146-


90&date=2011&title=Investigative+Ophthalmology+%26+Visual+Science&atitle=Quantitative+measure

ments+of+autofluorescence+with+the+scanning+laser+ophthalmoscope.&aulast=Delori&pid=%3Cautho

r%3EDelori+F%3BGreenberg+JP%3BWoods+RL%3BFischer+J%3BDuncker+T%3BSparrow+J%3BSmith+RT

%3C%2Fauthor%3E%3CAN%3E22016060%3C%2FAN%3E%3CDT%3EComparative+Study%3C%2FDT%3E.

Accessed 20111214.

14. Kim SR, Jang YP, Sparrow JR. Photooxidation of RPE lipofuscin bisretinoids enhances fluorescence

intensity. Vision Res Mar 31 2010;50(7):729-36. Available from: http://alliance-


&id=doi:10.1016%2Fj.visres.2009.09.015&issn=0042-


36&date=2010&title=Vision+Research&atitle=Photooxidation+of+RPE+lipofuscin+bisretinoids+enhances

+fluorescence+intensity.&aulast=Kim&pid=%3Cauthor%3EKim+SR%3BJang+YP%3BSparrow+JR%3C%2Fa

uthor%3E%3CAN%3E19800359%3C%2FAN%3E%3CDT%3EJournal+Article%3C%2FDT%3E. Accessed

20100316.

15. Feldman TB, Yakovleva MA, Dontsov AE, Ostrovsky MA. Fluorescence emission and excitation

spectra of fluorophores of lipofuscin granules isolated from retinal pigment epithelium of human

cadaver eyes. Russian Chemical Bulletin 2010;59(1):276 <last_page> 283.

16. Hunter JJ, Morgan JI, Merigan WH, Sliney DH, Sparrow JR, Williams DR. The susceptibility of the

retina to photochemical damage from visible light. Prog Retin Eye Res Jan 2012;31(1):28-42. Available

from:

http://sfxhosted.exlibrisgroup.com/pacificu?sid=OVID:medline&id=pmid:22085795&id=doi:10.1016%2F

j.preteyeres.2011.11.001&issn=1350-9462&isbn=&volume=31&issue=1&spage=28&pages=28-

42&date=2012&title=Progress+in+Retinal+%26+Eye+Research&atitle=The+susceptibility+of+the+retina+

to+photochemical+damage+from+visible+light.&aulast=Hunter&pid=%3Cauthor%3EHunter+JJ%3BMorg

an+JI%3BMerigan+WH%3BSliney+DH%3BSparrow+JR%3BWilliams+DR%3C%2Fauthor%3E%3CAN%3E22

085795%3C%2FAN%3E%3CDT%3EJournal+Article%3C%2FDT%3E. Accessed 20111219.

17. Morgan JI, Hunter JJ, Merigan WH, Williams DR. The reduction of retinal autofluorescence caused by

light exposure. Invest Ophthalmol Vis Sci Dec 2009;50(12):6015-22. Available from:

http://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&D=medl&AN=19628734.

18. Sparrow JR, Yoon KD, Wu Y, Yamamoto K. Interpretations of fundus autofluorescence from studies of

the bisretinoids of the retina. Invest Ophthalmol Vis Sci Sep 2010;51(9):4351-7. Available from:

http://alliance-


&id=doi:10.1167%2Fiovs.10-5852&issn=0146-


7&date=2010&title=Investigative+Ophthalmology+%26+Visual+Science&atitle=Interpretations+of+fund

us+autofluorescence+from+studies+of+the+bisretinoids+of+the+retina.&aulast=Sparrow&pid=%3Cauth

or%3ESparrow+JR%3BYoon+KD%3BWu+Y%3BYamamoto+K%3C%2Fauthor%3E%3CAN%3E20805567%3

C%2FAN%3E%3CDT%3EJournal+Article%3C%2FDT%3E. Accessed 20100831.

19. Yamamoto K, Zhou J, Hunter JJ, Williams DR, Sparrow JR. Toward an understanding of bisretinoid

autofluorescence bleaching and recovery. Invest Ophthalmol Vis Sci Jun 2012;53(7):3536-44. Available

from: http://alliance-


&id=doi:10.1167%2Fiovs.12-9535&issn=0146-


44&date=2012&title=Investigative+Ophthalmology+%26+Visual+Science&atitle=Toward+an+understand

ing+of+bisretinoid+autofluorescence+bleaching+and+recovery.&aulast=Yamamoto&pid=%3Cauthor%3E

Yamamoto+K%3BZhou+J%3BHunter+JJ%3BWilliams+DR%3BSparrow+JR%3C%2Fauthor%3E%3CAN%3E2

2570342%3C%2FAN%3E%3CDT%3EJournal+Article%3C%2FDT%3E. Accessed 20120611.

20. SPSS [computer program] - version 20. Chicago, IL. IBM corp; 2013.

21. Sparrow JR, Blonska A, Flynn E, Duncker T, Greenberg JP, Secondi R, Ueda K, Delori FC. Quantitative

fundus autofluorescence in mice: Correlation with HPLC quantitation of RPE lipofuscin and

measurement of retina outer nuclear layer thickness. Invest Ophthalmol Vis Sci 2013;54(4):2812-20.

Available from: http://alliance-


&id=doi:10.1167%2Fiovs.12-11490&issn=0146-


20&date=2013&title=Investigative+Ophthalmology+%26+Visual+Science&atitle=Quantitative+fundus+a

utofluorescence+in+mice%3A+correlation+with+HPLC+quantitation+of+RPE+lipofuscin+and+measurem

ent+of+retina+outer+nuclear+layer+thickness.&aulast=Sparrow&pid=%3Cauthor%3ESparrow+JR%3BBlo

nska+A%3BFlynn+E%3BDuncker+T%3BGreenberg+JP%3BSecondi+R%3BUeda+K%3BDelori+FC%3C%2Fau

thor%3E%3CAN%3E23548623%3C%2FAN%3E%3CDT%3EJournal+Article%3C%2FDT%3E. Accessed

20130418.

Appendix. R program to calculate mean luminance from autofluorescence photos. The

program used a mixture to compute the proportion of pixels, mean, and standard deviations of

two distributions within the file. The luminance attributed to lipofuscin was based on the mean

luminance of the brighter distribution calculating the mean luminance of the pixels of the pixels

greater than the mean of the second distribution.

R code

library(pixmap)

library(rtiff)

library(mixtools)

library(mixdist)

path<-c(

'd:/blue light/study data/Class 2012/Sept 10/Left/'

) */ For example

np<-length(path) # Number of folders to review. Each subject class has their own folder for

each eye

p=1

i=1

while (p<=np) # Go through each folder

{

eyepic=dir(path=path[p] ,pattern="*.tif",ignore.case=TRUE)

sort(eyepic)

ni<-length(eyepic)

###

pic_mixture<-function(i){

filename<-paste(path[p],sep="",eyepic[i])

#filename<-'d:/blue light/new baseline unfiltered/126 af 2.tif' # for example

getDescription(filename)

pic<-readTiff(filename)

plot(pic,main=path[p],sub=eyepic[i])

mat<-getChannels(pic)

mat<-sort((mat))

hist(mat)

mat<-mat*255

mat<-round(mat)

q1<-quantile(mat,probs=c(.05,.5,.999),na.rm=TRUE)

mat<-ifelse(mat>4&mat<q1[3],mat,NA) #Eliminate black corners and text on the photo

mat<-na.omit(mat)

q<-quantile(mat,probs=c(.05,.5,.9),na.rm=TRUE)

pi<-c(.05,.95)

mu<-c(structure(c(q[1],q[3]),names=NULL))

sigma<-c(.3*mu[1],.2*mu[2])

parms<-data.frame(pi,mu,sigma)

matdata=mixgroup(mat,breaks=200)

matmix<-as.mixdata(matdata)

fitmat1<-

mix(matmix,mixpar=parms,dist="gamma",constr=mixconstr(consigma="SFX",fixsigma=c(FALSE,

FALSE),conmu="MFX",fixmu=c(FALSE,FALSE)), iterlim=150)

x<-fitmat1[[1]]

dev.next()

plot(fitmat1)

plotname<-c(paste(substr(filename,1,nchar(filename)-4),sep="",".jpg"))

dev.copy(jpeg,plotname)

dev.off()

mat2<-ifelse(mat>x[[2,2]],mat,NA) #/select pixels > mean of the upper distribution

lipo<-mean(mat2,na.rm=TRUE)

id<-substr(eyepic[i],1,3)

eye<-1

#

line<-c(id,eye,lipo,q,x[[1]],x[[2]],x[[3]],fitmat1[[5]],fitmat1[[6]],filename)

#line<-c(id,eye,picnum,lipo,q,x[[1]],x[[2]],x[[3]],fitmat1[[5]],fitmat1[[6]],filename)

line

out<-paste( 'd:/blue light/lipo 20120510/',sep="","2012Sept10Left.txt")

write.table(t(line),out,append=TRUE,quote=FALSE,sep=",",row.names=FALSE,col.names=FALSE)

print(q)

fitmat1<-""

mat<-""

pic<-""

return(TRUE)

}

Impact of excess light and yellow filters on accumulation of lipofuscin … · 2017. 1. 5. ·...

Documents

Transcript of Impact of excess light and yellow filters on accumulation of lipofuscin … · 2017. 1. 5. ·...