- Open Access
Daily illumination exposure and melatonin: influence of ophthalmic dysfunction and sleep duration
Journal of Circadian Rhythms volume 3, Article number: 13 (2005)
Ocular pathology lessens light's efficacy to maintain optimal circadian entrainment. We examined whether ophthalmic dysfunction explains unique variance in melatonin excretion of older adults over and above the variance explained by daily illumination, medical, and sociodemographic factors. We also examined whether ophthalmic dysfunction influences relationships between ambient illumination and melatonin.
Thirty older adults (mean age = 69 years; Blacks = 42% and Whites = 58%) of both genders participated in the study. Demographic and health data were collected at baseline. Participants underwent eye exams at SUNY Downstate Medical Center, wore an actigraph to monitor illumination and sleep, and collected urine specimens to estimate aMT6s concentrations.
Hierarchical regression analysis showed that illumination factors explained 29% of the variance in aMT6s mesor. The proportion of variance explained by ophthalmic factors, sleep duration, and race was 10%, 2%, and 2%, respectively. Illumination factors explained 19% of the variance in aMT6s acrophase. The proportion of variance explained by ophthalmic factors, sleep duration, and race was 11%; 17%; and 2%, respectively. Controlling for sleep duration and race reduced the correlations between illumination and melatonin, whereas controlling for ophthalmic factors did not.
Ophthalmic exams showed that elevated intraocular pressure and large cup-to-disk ratios were independently associated with earlier melatonin timing. Lower illumination exposure also had independent associations with earlier melatonin timing. Conceivably, ophthalmic and illumination factors might have an additive effect on the timing of melatonin excretion, which in turn might predispose individuals to experience early morning awakenings.
Light influences numerous biological and behavioral functions [1–3]. In the laboratory, exposure to light of varying intensities, wavelengths, and durations entrains the circadian pacemaker , suppresses melatonin rhythms [2, 3, 5], and modulates pupillary reflexes [6–8]. Recent evidence suggests that these processes involve specialized signal transduction mechanisms of intrinsically photosensitive retinal ganglion cells . These cells are believed to express melanopsin, the primary candidate photopigment in the synchronization of circadian rhythms [7, 10–12].
Studies performed in the natural environment have shown that ambient illumination affects melatonin rhythms [13, 14], rest-activity cycles [15, 16], and mood [17, 18]. Naturalistic studies have also demonstrated that several factors impinge on the level and timing of ambient illumination. They include age , gender , race/ethnicity [15, 19], time standard , season [20–23], and latitude . Notwithstanding the importance of these factors, the integrity of the visual and photic system remains the overriding component governing light's ability to entrain circadian rhythms.
Generally, blind patients without conscious light perception show a loss of circadian entrainment and do not experience light-induced suppression of melatonin [2, 24–28]. Emerging evidence suggests, however, that a minority of blind patients maintain the capacity for photic entrainment, as demonstrated through melatonin-suppression tests [2, 25]. Thus, light transmission is not necessarily abolished in all patients with no conscious light perception, particularly where no optic diseases are suspected. A recent study, investigating adolescents and young adults ages 12–20 years from the Missouri School for the Blind, found significantly greater circadian dysfunction (e.g., more daytime napping and variable timing of awakening), among patients with optic diseases relative to those without such diseases . It appears that blind patients exhibiting incapacity for photic entrainment represent a unique category.
Much less is known regarding effects of age-related photic impairment on circadian rhythm functions. There are suggestions that several ophthalmic diseases could attenuate photic transmission to the circadian pacemaker. Senile miosis is one of those diseases; it is characterized by an age-related reduction in pupil diameter that could reduce retinal illumination [6, 30]. Opacification and yellowing of the crystalline lens of the eye, as seen in patients with cataracts, can also substantially reduce photic transmission . Loss of retinal ganglion cells, which afflicts primarily glaucoma patients, might negatively affect retinal phototransduction to the pacemaker [32, 33].
It of great interest to ascertain how each of these ophthalmic diseases compromises light input to the circadian system. Judging from the available evidence, it is reasonable to hypothesize that age-associated ocular pathology lessens light's efficacy to maintain optimal circadian entrainment [34–36]. In the present study, we tested the hypothesis that ophthalmic dysfunction explains unique variance in melatonin excretion of older adults over and above that explained by daily illumination, medical, and sociodemographic factors. A parallel hypothesis examined in this study was that ophthalmic dysfunction influences the relationships between ambient illumination and endogenous melatonin rhythms.
Data presented in this paper were from a study investigating relations of ambient illumination to depression and melatonin excretion. Associations of daily illumination exposure with depression have been reported elsewhere . The present report focuses on relationships of daily illumination and ophthalmic measures to melatonin excretion.
Respondents to study advertisements completed baseline questionnaires. They were included if they had no current eye diagnosis, their self-stated race was Black or White, were 60 years old or older, and provided informed consent under the supervision of the Institutional Review Boards at SUNY and UCSD. They were excluded if they indicated major depression or lithium use, sleep apnea, drugs that influence endogenous melatonin, a history of ocular surgery or laser treatment, or impaired cognitive or functional ability. Respondents were compensated for participating in the study.
Volunteers meeting study criteria provided demographic and health-related data, underwent eye exams, provided illumination and sleep data, and collected urine specimens. Thirty participants (mean age = 69.03 ± 6.84 years) provided complete data for the present analyses. The sample comprised Black (43%) and White (57%) Americans of both genders (women = 80% and men = 20%), with a BMI averaging 26.89 ± 6.11 kg/m2; 87% received at least a high school diploma and the median household income was $16,500.
Baseline data were acquired using the Comprehensive Assessment and Referral Evaluation (CARE), the 30-item Geriatric Depression Scale (GDS), and the Pittsburgh Sleep Quality Index (PSQI). The CARE has been widely used to assess physical health of older individuals in minority communities. It has shown good construct validity  as well as concurrent and predictive validity . Five sub-scales were included in the present analysis: vision disorder, respiratory disease, diabetes, hypertension, and sleep disorder (Cronbach α = 0.78; 0.86; 0.82; 0.91; and 0.92, respectively).
The GDS measures depressed moods. It comprises five main factors described as: sad mood, lack of energy, positive mood, agitation, and social withdrawal. According to a study that examined depressed moods among adults (≥ 60 years old) attending primary-care clinics, the GDS had a sensitivity of 100% and a specificity of 84% in screening for major depression, using a cut-off score of 10 . By contrast, the original psychometric study, which used a cut-off score of 11, found a sensitivity of 81% and a specificity of 61% for major depression (DSMIII-R) .
Although the PSQI is not highly specific, it is a valid measure of subjective sleep quality in clinical research. A psychometric study has shown good overall reliability coefficient for the PSQI (Cronbach α = 0.77) . When investigators used a cut-off point of 5.5 in the global score, sensitivity and specificity estimates were respectively 85.7% and 86.6% for primary insomnia, 80.0% and 86.6% for major depression, 83.3% and 86.6% for generalized anxiety disorder, and 83.3% and 86.6% for schizophrenia. Nonetheless, this scale does not necessarily distinguish between conditions disturbing subjective sleep.
A trained technician performed standard examinations to assess ophthalmic disorders. These provided data on visual acuity, visual field defects (mean deviation), intraocular pressure (IOP), vertical and horizontal cup-to-disk ratios (CDR), and nerve-fiber-layer (NFL) thickness; a large CDR is an indicator of glaucoma. An ophthalmologist graded ocular photos.
Snellen best-corrected visual acuity was obtained and converted into logMAR units; higher scores denoted worse visual acuity. The SITA standard program of the Humphrey Field Analyzer was used for visual field testing to estimate ocular nerve loss . Results of the Ocular Hypertension Treatment Study suggested that 97% of visual field examinations are reliable . Tonometry was used to assess intraocular pressure [44, 45]. The Egna-Neumarkt Glaucoma study revealed that the sensitivity and specificity of tonometry in recognizing glaucoma are 80% and 98%, respectively . Fundus photography was used to examine the retina and the macula . Vertical and horizontal CDR in the optic disk were derived, with higher scores indicating greater abnormality. According to the Early Treatment Diabetic Retinopathy Study, agreement rates range from 78% to 83% between retinal specialists and photographic graders . Peripapillary NFL thickness, a measure of atrophy of the retinal ganglion cells, was assessed with a scanning laser polarimeter (Nerve Fiber Analyzer GDX) . The GDX can detect glaucomatous eyes with a sensitivity of 71% and a specificity of 91% .
Illumination and sleep assessment
Upon completion of eye exams, participants wore the Actiwatch-L (Mini Mitter Co., Inc.) for a week at home to monitor ambient illumination and sleep. The Actiwatch-L is a monitoring device worn on the wrist, which incorporates a photometer and a linear accelerometer. The photometer registers illumination that ranges from 1 to 150,000 lux. Registered lux values are averaged across each minute and stored in memory.
Illumination time-series data were imported into a computer program for least-squares cosine analyses using Action3 software. This technique is preferred because it corrects for biases due to the time of day when the recordings began and for missing data due to actigraph removal. Cosine analyses were performed on the logarithm of measured illumination. Derived circadian measures were: 1) the mesor, the fitted 24-hour average of logged illumination levels and 2) the acrophase, the timing of the peak of the fitted cosine; goodness of fit for the cosines averaged 0.65 ± 0.12. Acrophases could be linearized before performing statistical analyses, since their distribution did not cover the whole range of 360 degrees.
The accelerometer of the Actiwatch-L is sensitive to 0.01 g. and has a sampling frequency of 32 Hz; it summates and records the degree and intensity of motion on a minute-by-minute basis. Actigraphic sleep time was estimated using an automatic algorithm provided by the Actiwatch manufacturer . Acceptable correlations have been found between actigraphic and polysomnographic estimates of sleep duration, but the accuracy of the algorithm has not been systematically ascertained for use among older adults. Illumination and sleep log data were used to verify time-in-bed intervals before estimating sleep and wakefulness. Sleep duration was averaged across all seven days, and this was used as a measure of habitual sleep time.
Urine samples were collected for approximately 24 hours near the end of the Actiwatch-L recording. Participants collected each fractional urine specimen, measured and recorded its time and total volume, and froze duplicate aliquots in two 2 cc vials. Most volunteers provided the required 10 samples spanning at least 24 hours, and most included at least one mid-sleep collection. Samples were retrieved by a staff member and sent to UCSD where they were stored at -70°C until assay of 6-sulfatoxymelatonin (aMT6s), the major urinary melatonin metabolite using 96 well ELISA kits (Buhlmann Labs, EK-M6S) purchased from ALPCO, Ltd. (Windham, NH). This is a competitive immunoassay that uses a highly specific rabbit anti-6-sulfatoxymelatonin antibody and a second antibody capture technique. Assay performance has been extensively validated by the manufacturer and results correlate well with the Arendt (Stockgrand, Ltd) RIA (r = 0.987). At the usual dilution of 1:200 the analytical sensitivity of the ELISA is 0.35 ng/ml and the functional least detectable dose (for CV < 20%) is 1.3 ng/ml. In our laboratory, control urine samples averaging 4–6 ng/ml give intra- and inter-assay CVs of 4% and 7%, respectively.
To ensure reliability of the aMT6s data, we visually analyzed excretion curves of all participants to record an overall quality score for each 24-hour profile. This evaluation was performed blind to all other information about the participants and was mainly based on the shape and completeness of the ng/h curve, but agreement between ng/h and ng/ml temporal patterns, smoothness of the baseline, and reliability of the patient log were also considered. As a circadian pattern that is clear and free of irregularities is required to estimate acrophase reliably, onset, and offset, profiles with poor quality scores were excluded. Accordingly, we selected 30 suitable profiles from a total of 59 considered. Data excluded from the final batch were not assayed due mostly to missing samples or inaccurate record keeping. Volunteers providing complete melatonin data were not significantly different in clinical presentation compared to those who did not. Of note, Blacks provided a greater number of unusable melatonin samples.
The aMT6s excretion rate for each urine sample was computed and transformed into 5-min epoch data and the resulting time series data were imported into Action3 software (Ambulatory Monitoring Inc., Ardsley, NY), where they were aligned with illumination data and further checked for accuracy. Twenty-four-hour least-squares cosine fits were computed for the full aMT6s collection (average duration, excluding missing data intervals was 24.00 h) yielding aMT6s mesors and acrophases. To estimate the duration of nocturnal aMT6s excretion, the onset and the offset of the excretion were estimated by interpolation of times at which the excretion rate (ng/h) crossed the mesor level. The time of onset of aMT6s excretion was estimated as the upward crossing and offset as the downward crossing of the mesor level; aMT6s duration was defined as the interval between onset and offset times. Goodness of fit for the cosines averaged 0.81 ± 0.11.
All acquired data were merged into SPSS 10.0 for final analyses. These included ophthalmic, sociodemographic, medical, mood, illumination, sleep, and melatonin data. Distributions were checked for normality and were transformed where necessary using appropriate statistical techniques. Frequency and measures of central tendency were used to describe the sample. MANCOVA was used to examine race effects on ophthalmic, illumination, sleep, and melatonin measures. This procedure allowed correction for multicolinearity, if detected, and adjustment for multiple comparisons.
To examine which factors were predictive of the dependent variables: aMT6s mesor (fitted mean) and acrophase (timing), we employed two hierarchical regression models. This statistical modeling technique yields the proportion of variance in the dependent variable that can be explained by an additional set of factors, over and above that explained by the initial set. Accordingly, one can opt to use the restricted model component, providing results only for the initial set. One can also use the expanded model, which sequentially analyzes the independent contribution of additional sets. In the present analysis, the initial set comprised the mesor and the acrophase of illumination. Three other sets of factors: demographic, medical, and ophthalmic were entered in a stepwise manner. The first regression model used aMT6s mesor as the dependent variable and the illumination data plus three sets of factors as predictors. In the second model, aMT6s acrophase timing was used as the dependent variable, and the above factors were entered as in the first model.
Factors in these analyses were chosen because of their associations with the dependent measures and/or because of their hypothesized connection to melatonin. The selection process was based on preliminary results of the Pearson and Spearman correlations that were run to examine the magnitude of the correlation between each factor and the dependent variables and by examination of their collinearity. Results of these preliminary analyses revealed that race/ethnicity was the most important factor for the sociodemographic set (i.e., age, sex, race, education, and income). Of the medical set (BMI, hypertension, diabetes, mood, sleep duration, and sleep quality), sleep duration was chosen. Of the ophthalmic set (i.e., visual acuity, CDR ratios, IOP, visual fields mean deviation, and NFL thickness), IOP and horizontal CDR were selected; these two factors were chosen because they showed similar coefficients and because of their theoretical importance as indicators of glaucoma in the regression model.
To assess whether associations between illumination and melatonin were mediated by ophthalmic factors, partial correlations were used. In that analysis, the ophthalmic factors were controlled. In separate partial correlation analyses, effects of the demographic and medical factors were controlled.
Most participants (79%) were in good health. None were legally blind, but 30% were visually impaired based on standard criteria (best corrected vision worse than 20/40 and better than 20/200 in the better eye) . Of the sample, 83% reported being satisfied with their sleep, although 61% indicated either difficulty initiating sleep, difficulty maintaining sleep, early morning awakening, or daytime napping. Moreover, 23% reported a respiratory condition, 60% hypertension, 77% arthritis, 43% vision problems, and 14% diabetes. Fifty-two percent reported social drinking, 15% indicated consumption of sleep aids, and 7% were current smokers.
On average, volunteers had a GDS score of 7.07 ± 3.69 and a PSQI score of 4.68 ± 2.80. Subjective and actigraphic estimates of total sleep time averaged 6.40 ± 1.04 hours and 7.55 ± 1.74 hours, respectively. Median ambient illumination was 565.68 lux. Median aMT6s excretion was 324.60 ng/h. The medians for the acrophases of illumination and aMT6s were 14.12 hours and 3.18 hours (after midnight), respectively. As seen in Table 1, race had significant effects on ophthalmic measures, indicating greater ophthalmic dysfunction for Blacks. In Table 2, we present results of race effects on illumination, melatonin, and sleep measures.
Analysis indicated that the mesor and the acrophase of aMT6s were both associated with the sociodemographic, medical, and ophthalmic factors. The multiple correlation (r2) of aMT6s mesor to these factors added individually was: [r2 = 0.24; r2 = 0.23; r2 = 0.15, respectively]; for aMT6s acrophase, it was: [r2 = 0.15; r2 = 0.21; r2 = 0.28, respectively]. However, in the interest of developing parsimonious regression models and because our sample was too small for a detailed analysis of the overlapping effects of all of the factors on the dependent variables, we selected representative factors from each set of factors. Accordingly, besides the mesor and acrophase of illumination only race, sleep duration, CDR and IOP were entered into the hierarchical regression models as predictors. With a sample size of 30 and an alpha value set at 0.05, it was determined a priori that the study would have power of 0.85 to construct a reliable model with six predictors, accounting for 41% of the variance in the dependent variable.
Results of the first hierarchical regression analysis showed that illumination factors explained 29% of the variance in aMT6s mesor; illumination acrophase was the main contributor, indicating that individuals showing later timing had lower aMT6s mesors. Sequential addition of the other factors (i.e., CDR and IOP, entered as a set, sleep duration, and race) showed that the proportion of variance explained by each was 10%, 2%, and 2%, respectively. Overall, the expanded model accounted for 43% of the variance in aMT6s mesor [F = 3.47, p < 0.05]. The adjusted stepwise correlations of each of the factors to aMT6s mesor were: illumination mesor [rp = -0.08], illumination acrophase [rp = -0.49], race [rp = -0.08], sleep duration [rp = -0.25], IOP [rp = 0.31], and CDR [rp = -0.25]. For each of these correlations, effects of the other five factors were simultaneously adjusted.
In the second hierarchical regression analysis, where aMT6s acrophase was the dependent variable, the illumination factors explained 19% of the variance; individuals receiving greater daily illumination level and showing later illumination timing were likely to show later aMT6s timing. The proportion of variance explained by the factors: CDR and IOP (entered as a set), sleep duration, and race was 11%; 17%; and 2%, respectively. Altogether, the expanded model accounted for 49% of the variance in aMT6s acrophase [F = 2.64, p < 0.05]. The adjusted stepwise correlations of each of the factors to aMT6s acrophase were: illumination mesor [rp = 0.41], illumination acrophase [rp = 0.09], race [rp = -0.03], sleep duration [rp = 0.48], IOP [rp = -0.29], and CDR [rp = -0.32].
In Table 3, we present results of the partial correlation analyses, examining associations of illumination factors with melatonin measures. Consistent with regression results, later timing of illumination was significantly associated with lower aMT6s mesor. Controlling for sleep duration and race somewhat reduced this association, whereas controlling for IOP and CDR affected them little. Trends suggested that greater illumination was associated with later aMT6s timing.
The data show that ophthalmic dysfunction was associated with the endogenous melatonin rhythms of community-residing older adults. Ophthalmic factors explained a significant proportion of the variance in 24-hr 6-sulphatoxymelatonin excretion (mesor) and timing (acrophase), over and above the variance explained by daily illumination, sleep duration, and race. Although most of the volunteers were in good health, ophthalmic exams showed significant evidence of photic impairment anchored by elevated intraocular pressure and large cup-to-disk ratios, which were independently associated with earlier melatonin timing. We observed that lower illumination levels also had independent associations with earlier melatonin timing. Conceivably, ophthalmic and illumination factors might have an additive effect on the timing of melatonin excretion, which in turn might predispose individuals to experience early morning awakenings.
As greater intraocular pressure and cup-to-disk ratio may be indicative of optic nerve loss, a common finding among glaucoma patients , their effects on melatonin rhythms might be mediated by a defect in retinohypothalamic stimulation. Unfortunately, this study did not offer direct support for this hypothesis. Ophthalmic dysfunction does not seem to have a mediating effect on the relationships between ambient illumination and melatonin rhythms, as these relationships remained virtually unchanged when we controlled for differences in ophthalmic factors. Hence, abnormalities in both IOP and CDR may have had a direct effect on the timing of melatonin excretion of White and Black participants. However, associations of IOP and CDR with the amount of melatonin excretion were mixed, with greater IOP predicting greater excretion while greater CDR predicted lower excretion rates, which was in the expected direction. This discrepancy merits further examination, but we might consider that previous studies of melatonin rhythms in uncontrolled environments have shown that the acrophase, rather than the mesor of melatonin excretion, strongly correlated to ambient illumination , depression scores , activity rhythms , napping behavior , and duration and timing of sleep [52, 54].
Habitual illumination pattern was the best predictor of aMT6s rhythms of all the factors in the regression models. Both brighter and later illumination exposure correlated to later aMT6s timing, although illumination level was a better predictor in the regression model. We noted that the timing of illumination exposure, rather than its mesor, correlated significantly to the mesor of aMT6s. It might be that a later illumination acrophase reflects less illumination exposure in the morning before the endogenously timed offset of melatonin secretion. Therefore, a later illumination acrophase might be associated with less morning light suppression of melatonin and, in turn, a delayed acrophase of aMT6s excretion.
The timing of daily illumination might be a better index of the amount of aMT6s excretion, irrespective of individuals' sociodemographic and medical characteristics. Evidently, this must be balanced against the observation that the timing of melatonin excretion can be influenced by age-related weakening of the circadian pacemaker as well as by individual preferences in the timing of outdoor daylight activities [55–57]. Other factors influencing melatonin excretion in the natural setting include day length, age, duration and timing of sleep, and usage of certain medications [13, 16, 19, 23, 58]. Our analysis considered the relative contribution of all these factors, except for day length (season), but scheduling of the recordings was balanced across seasons throughout the study period.
Sleep duration is another factor that played an important role in the analyses. That sleep duration correlated with both the mesor and the acrophase of aMT6s is consistent with previous findings [59–61]. We would have expected that shorter sleep duration would correlate with reduced aMT6s excretion, as predicted by data suggesting a longer experience of nocturnal darkness (as might be associated with a longer sleep duration) results in a longer duration of melatonin excretion . The inverse correlation found in our study may have been influenced by the finding that Blacks slept less than did Whites while showing greater mesors of aMT6s excretion. It is noteworthy that in our preliminary analyses aMT6s measures had stronger correlations to sleep duration than to a history of hypertension, diabetes, or respiratory disease, BMI, mood or sleep quality. Possibly, sleep duration is a proxy for these measures, as it correlates to each, albeit to varying degrees.
Of all the sociodemographic factors we analyzed, race was the strongest correlate of aMT6s measures. This is consistent with results of the analysis of covariance reported in Table 2. Independent of individuals' age and gender, race had significant effects on the melatonin measures. Similarly, race had significant effects on the ophthalmic, illumination, and sleep variables. These findings evidence that race is an important factor when analyzing sleep and circadian rhythm measures. Notwithstanding, it is less robust than the illumination, sleep, and ophthalmic factors in explaining the variance in aMT6s measures. One explanation for the reduced significance of race in the regression models relates to the shared variance in aMT6s measures explained by both race and these other factors.
Consistent with previous epidemiological and clinical data, individuals of the Black race showed worse scores on ophthalmic exams [63, 64]. A thinner nerve fiber layer, an elevated intraocular pressure, and greater cup-to-disk ratios, as observed among Blacks, are three important indicators of optic nerve loss in glaucoma. One implication of these findings is that since glaucoma is more common among Blacks [65, 66], they may be at increased risks of developing circadian abnormalities through reduction of photic transduction to the circadian pacemaker.
Since we used a relatively small sample size, we could not assess the overlapping effects of all the independent factors on melatonin rhythms. It was evident that daily illumination, ophthalmic factors, sleep duration, and race each had independent associations with both the mesors and acrophases of melatonin excretion. Although our regression models approximated predictions of the power analysis, they warrant replication in a larger sample. Efforts should be made to provide detailed instructions in gathering melatonin samples among minority groups. The observation that Blacks had lower illumination exposure, greater ophthalmic dysfunction, and higher aMT6s levels merits further empirical study, as these characteristics are suggestive of depressed moods [18, 51, 58, 67].
Hollick MF, Jung EG: Biologic effects of light. (Edited by: Hollick MF and Jung EG). Norwell, MA, Kluwer Academic Publishers 1998.
Czeisler CA, Shanahan TL, Klerman EB, Martens H, Brotman DJ, Emens JS, Klein T, Rizzo JF: Suppression of melatonin secretion in some blind patients by exposure to bright light [see comments]. N Engl J Med 1995, 332:6–11.
Czeisler CA: The effect of light on the human circadian pacemaker. Ciba Found Symp 1995, 183:254–290.
Czeisler CA, Allan JS, Strogatz SH, Ronda JM, Sánchez R, Ríos CD, Freitag WO, Richardson GS, Kronauer RE: Bright light resets the human circadian pacemaker independent of the timing of the sleep-wake cycle. Science 1986, 8:667–671.
Lewy AJ, Wehr TA, Goodwin FK, Newsome DA, Markey SP: Light suppresses melatonin secretion in humans. Science 1980, 210:1267–1269.
Gaddy JR, Ruberg FL, Brainard GC, Rollag MD: Pupillary modulation of light-induced melatonin suppression. Biologic effects of light (Edited by: Jung EG and Holick MF). Berlin, Walter de Gruyter & Co. 1994, 159–168.
Panda S, Nayak SK, Campo B, Walker JR, Hogenesch JB, Jegla T: Illumination of the melanopsin signaling pathway. Science 2005, 307:600–604.
Hattar S, Lucas RJ, Mrosovsky N, Thompson S, Douglas RH, Hankins MW, Lem J, Biel M, Hofmann F, Foster RG, Yau KW: Melanopsin and rod-cone photoreceptive systems account for all major accessory visual functions in mice. Nature 2003, 424:76–81.
Berson DM, Dunn FA, Takao M: Phototransduction by retinal ganglion cells that set the circadian clock. Science 2002, 295:1070–1073.
Sakamoto K, Liu C, Tosini G: Classical photoreceptors regulate melanopsin mRNA levels in the rat retina. J Neurosci 2004, 24:9693–9697.
Provencio I, Rodriguez IR, Jiang G, Hayes WP, Moreira EF, Rollag MD: A novel human opsin in the inner retina. J Neurosci 2000, 20:600–605.
Sekaran S, Lupi D, Jones SL, Sheely CJ, Hattar S, Yau KW, Lucas RJ, Foster RG, Hankins MW: Melanopsin-dependent photoreception provides earliest light detection in the mammalian retina. Curr Biol 2005, 15:1099–1107.
Youngstedt SD, Kripke DF, Elliott JA: Circadian phases of illumination and melatonin are associated. Sleep Research 1997, 26:760.
M D: Light exposure and melatonin secretion in shiftworkers. Biologic effects of light. (Edited by: Hollick MF and Jung EG). Norwell, MA, Kluwer Academic Publishers 1998, 437–446.
Kripke DF, Jean-Louis G, Elliott JA, Klauber MR, Rex KM, Tuunainen A, Langer RD: Ethnicity, sleep, mood, and illumination in postmenopausal women. BMC Psychiatry 2004, 4:8–9.
Jean-Louis G, Kripke DF, Ancoli-Israel S, Klauber M, Sepulveda RS, Mowen MA, Assmus JD, Langer RD: Circadian sleep, illumination, and activity patterns in women: Influences of aging and time reference. Physiol Behav 2000, 68:347–352.
Espiritu RC, Kripke DF, Ancoli-Israel S, Mowen MA, Mason WJ, Fell RL, Klauber MR, Kaplan OJ: Low illumination experienced by San Diego adults: association with atypical depressive symptoms. Biol Psychiatry 1994, 106:780–786.
Jean-Louis G, Kripke D, Cohen C, Zizi F, Wolintz A: Associations of Ambient Illumination With Mood: Contribution of Ophthalmic Dysfunctions. Physiol Behav 2005, 84:479–487.
Jean-Louis G, Kripke DF, Ancoli-Israel S, Klauber M, Sepulveda RS: Sleep duration, illumination, and activity patterns in a population sample: Effects of gender and ethnicity. Biol Psychiatry 2000, 47:921–927.
Cole RJ, Kripke DF, Wisbey J, Mason WJ, Gruen W, Hauri PJ, Juarez S: Seasonal variation in human illumination exposure at two different latitudes. J Biol Rhythms 1995, 10:324–334.
Hebert M, Dumont M, Paquet J: Seasonal and diurnal patterns of human illumination under natural conditions. Chronobiol Int 1998, 15:59–70.
Guillemette J, Hebert M, Paquet J, Dumont M: Natural bright light exposure in the summer and winter in subjects with and without complaints of seasonal mood variations. Biol Psychiatry 1998, 44:622–628.
Eastman CI: Natural summer and winter sunlight exposure patterns in seasonal affective disorder. Physiol Behav 1990, 48:611–616.
Lockley SW, Skene DJ, Arendt J, Tabandeh H, Bird AC, Defrance R: Relationship between melatonin rhythms and visual loss in the blind. J Clin Endocrinol Metab 1997, 82:3763–3770.
Klerman EB, Shanahan TL, Brotman DJ, Rimmer DW, Emens JS, Rizzo JFIII, Czeisler CA: Photic resetting of the human circadian pacemaker in the absence of conscious vision. J Biol Rhythms 2002, 17:548–555.
Sack RL, Lewy AJ, Blood ML, Keith LD, Nakagawa H: Circadian rhythm abnormalities in totally blind people: Incidence and clinical significance. J Clin Endocrinol Metab 1992, 75:127–134.
Skene D, Lockley S, Arendt J: Melatonin in Circadian Sleep Disorders in the Blind. Biol Signals 1999, 8:90–95.
Klein T, Martens H, Dijk DJ, Kronauer RE, Seely EW, Czeisler CA: Circadian sleep regulation in the absence of light perception: chronic non-24-hour circadian rhythm sleep disorder in a blind man with a regular 24-hour sleep-wake schedule. Sleep 1993, 16:333–343.
Wee R, Van Gelder RN: Sleep disturbances in young subjects with visual dysfunction. Ophthalmology 2004, 111:297–302.
Gaddy JR, Rollag MD, Brainard GC: Pupil size regulation of threshold of light-induced melatonin suppression. Journal of Clinical Endocrinolology and Metabolism 1993, 77:1398–1401.
Brainard GC, Gaddy JR, Ruberg FM, Barker FM, Hanifin JP, Rollag MD: Ocular mechanisms that regulate the human pineal gland. (Edited by: Moller M and Pevet P). London, John Libby & Company Ltd. 1994, 415–432.
Blumenthal EZ, Weinreb RN: Assessment of the retinal nerve fiber layer in clinical trials of glaucoma neuroprotection. Surv Ophthalmol 2001, 45 Suppl 3:S305-S312.
Hannibal J, Hindersson P, Ostergaard J, Georg B, Hegge FW: Melanopsin is expressed in PACAp containing retinal ganglion cells of the human retinohypothalamic tract. Social Light Treatment Biol Rhythms Abst 2004, 159.
Czeisler CA, Richardson GS, Zimmerman JC, Moore-Ede MC, Weitzman ED: Entrainment of human circadian rhythms by light-dark cycles: a reassessment. Photochem Photobiol 1980, 34:239–247.
Morin LP: The circadian visual system. Brain Res Brain Res Rev 1994, 19:102–127.
Myers BL, Badia P: Changes in circadian rhythms and sleep quality with aging: mechanisms and interventions [published erratum appears in Neurosci Biobehav Rev 1996 Summer;20(2):I-IV]. Neurosci Biobehav Rev 1995, 19:553–571.
Teresi JA, Golden RR, Gurland BJ, Wilder DE, Bennett RG: Construct validity of indicator-scales developed from the Comprehensive Assessment and Referral Evaluation interview schedule. J Gerontol 1984, 39:147–157.
Teresi JA, Golden RR, Gurland BJ: Concurrent and predictive validity of indicator scales developed for the Comprehensive Assessment and Referral Evaluation interview schedule. J Gerontol 1984, 39:158–165.
Lyness JM , Noel TK , Cox CFAU, King DA, Conwell Y, CRaine ED: Screening for depression in elderly primary care patients. A comparison of the Center for Epidemiologic Studies-Depression Scale and the Geriatric Depression Scale. Arch Intern Med 1997, 157:449–554.
Burke WJ, Nitcher RL, Roccaforte WH, Wengel SP: A prospective evaluation of the Geriatric Depression Scale in an outpatient geriatric assessment center. J Am Geriatr Soc 1992, 40:1227–1230.
Doi Y, Minowa M, Uchiyama M, Okawa M, Kim K, Shibui K, Kamei Y: Psychometric assessment of subjective sleep quality using the Japanese version of the Pittsburgh Sleep Quality Index (PSQI-J) in psychiatric disordered and control subjects. Psychiatry Res 2000, 97:165–172.
Bass SJ, Feldman J: Visual-field defects in well-defined retinal lesions using Humphrey and Dicon perimeters [In Process Citation]. Optometry 2000, 71:643–652.
Johnson CA, Keltner JL, Cello KE, Edwards M, Kass MA, Gordon MO, Budenz DL, Gaasterland DE, Werner E: Baseline visual field characteristics in the ocular hypertension treatment study. Ophthalmology 2002, 109:432–437.
Bonomi L, Marchini G, Marraffa M, Morbio R: The Relationship between Intraocular Pressure and Glaucoma in a Defined Population. data from the egna-neumarkt glaucoma study. Ophthalmologica 2001, 215:34–38.
Dandona L, Dandona R, Naduvilath TJ, McCarty CA, Mandal P, Srinivas M, Nanda A, Rao GN: Population-based assessment of the outcome of cataract surgery in an urban population in southern India. Am J Ophthalmol 1999, 127:650–658.
Kinyoun J, Barton F, Fisher M, Hubbard L, Aiello L, Ferris FIII: Detection of diabetic macular edema. Ophthalmoscopy versus photography--Early Treatment Diabetic Retinopathy Study Report Number 5. The ETDRS Research Group. Ophthalmology 1989, 96:746–750.
Weinreb RN, Dreher AW, Coleman A, Quigley H, Shaw B, Reiter K: Histopathologic validation of Fourier-ellipsometry measurements of retinal nerve fiber layer thickness. Arch Ophthalmol 1990, 108:557–560.
Medeiros FA, Susanna RJ: Comparison of algorithms for detection of localised nerve fibre layer defects using scanning laser polarimetry. Br J Ophthalmol 2003, 87:413–419.
Kushida CA, Chang A, Gadkary C, Guilleminault C, Carrillo O, Dement WC: Comparison of actigraphic, polysomnographic, and subjective assessment of sleep parameters in sleep-disordered patients. Sleep Med 2001, 2:389–396.
Tielsch JM, Sommer A, Witt K, Katz J, Royall RM: Blindness and visual impairment in an American urban population. The Baltimore Eye Survey. Arch Ophthalmol 1990, 108:286–290.
Tuunainen A, Kripke DF, Elliott JA, Assmus JD, Rex KM, Klauber MR, Langer RD: Depression and endogenous melatonin in postmenopausal women. J Affect Disord 2002, 69:149–158.
Lockley SW, Skene DJ, Butler LJ, Arendt J: Sleep and activity rhythms are related to circadian phase in the blind. Sleep 1999, 22:616–623.
IY Y, DF K, JA E, Langer RD: Naps and circadian rhythms in postmenopausal women. J Gerontol A Biol Sci Med Sci 2004, 59:844–848.
Kripke DF, Jean-Louis G, Assmus JD: Low illumination associated with poor mood and disturbed sleep. SLTBR 1999, 33:8–8.
Reiter RJ, Richardson BA: Some perturbations that disturb the circadian melatonin rhythm. Chronobiol Int 1992, 9:314–321.
Siegmund R, Tittel M, Schiefenhovel W: Activity Monitoring of the inhabitants of Tauwema, a traditional Melanesian village: rest/activity behavior of Trobriand Islands Papua New Guinea. Biologiacl Rhythm Research 1998, 29:49–59.
Swaab DF, Hofman MA, Lucassen PJ, Purba JS, Raadsheer FC, Van de Nes JA: Functional neuroanatomy and neuropathology of the human hypothalamus. Anat Embryol (Berl) 1993, 187:317–330.
Youngstedt SD, Kripke DF, Elliot JA, Baehr EK, Sepulveda RS: Light exposure, sleep quality, and depression in older adults. Biologic effects of light. (Edited by: Hollick MF and Jung EG). Norwell, MA, Kluver Academic Publishers 1998, 427–435.
Hajak G, Rodenbeck A, Staedt J, Bandelow B, Huether G, Rüther E: Nocturnal plasma melatonin levels in patients suffering from chronic primary insomnia. J Pineal Res 1993, 15:191–198.
Tzischinsky O, Shlitner A, Lavie P: The association between the nocturnal sleep gate and nocturnal onset of urinary 6-sulfatoxymelatonin. Acta Psychiatr Scand 1994, 89:1–7.
Leger D, Laudon MFAU, Zisapel N: Nocturnal 6-sulfatoxymelatonin excretion in insomnia and its relation to the response to melatonin replacement therapy. Am J Med 2004, 116:91–95.
Wehr TA: The durations of human melatonin secretion and sleep respond to changes in daylength (photoperiod). Brain Res 1995, 688:77–85.
Varma R, Tielsch JM, Quigley HA, Hilton SC, Katz J, Spaeth GL, Sommer A: Race-, age-, gender-, and refractive error-related differences in the normal optic disc. Arch Ophthalmol 1994, 112:1068–1076.
Chi T, Ritch R, Pitaman B, Stickler D, Tsai C, Hsieh FY: Racial differences in optic nerve head parameters. Arch Ophthalmol 1989, 107:836–839.
National Eye Institute Vision Report. Vision Problems in the U.S.: Prevalence of adult vision impairment and age-related eye disease in America (2002). http://www.nei.nih.gov/eyedata/pdf/VPUS.pdf. Accessed 05/28/02. 2002.
Leske MC, Connell AM, Wu SY, Nemesure B, Li X, Schachat A, Hennis A: Incidence of open-angle glaucoma: the Barbados Eye Studies. The Barbados Eye Studies Group. Arch Ophthalmol 2001, 119:89–95.
Tsai SY, Cheng CY, Hsu WM, Su TP, Liu JH, Chou P: Association between visual impairment and depression in the elderly. J Formos Med Assoc 2003, 102:86–90.
This research was supported by NIA (AG12364-07S1). We thank Dr. E. Leung, Dr. T. Brevetti, and J. Pierre-Louis for their assistance in the study.
The author(s) declare that they have no competing interests.
GJL supervised volunteer recruitment, data collection, data analysis, and drafting of the manuscript.
DFK helped design the study and assisted in data analysis and drafting of the manuscript.
JAE performed aMT6s assays and assisted in the drafting of the manuscript.
WAH participated in the analysis and interpretation of the ophthalmic data; he also assisted in the drafting of the manuscript.
LDR helped with the interpretation of the ophthalmic data and with the drafting of the manuscript.
All authors read and approved the final manuscript.
About this article
Cite this article
Jean-Louis, G., Kripke, D.F., Elliott, J.A. et al. Daily illumination exposure and melatonin: influence of ophthalmic dysfunction and sleep duration. J Circad Rhythms 3, 13 (2005). https://doi.org/10.1186/1740-3391-3-13