title: Relationships between 24h observations in intraocular pressure vs blood pressure, heart rate, nitric oxide and age in the medical chronobiology aging project.
abstract: OBJECTIVE
  To evaluate associations between intraocular pressure (IOP) and blood pressure (BP), heart rate (HR), serum nitric oxide (NO), diurnal variations, diabetes and aging in data collected during 24h studies of men conducted over 34y.
  
  
  METHODS
  As part of the Medical Chronobiology Aging Project, male Army veterans, ages 22 to 81y, without a history of eye disease, were studied around-the-clock in May 1969 (n = 13), 1979 (n = 11), 1988 (n = 11), 1993 (n = 11), 1998 (n =12) and 2003 (n = 10). Measurements of IOP (R & L eyes, supine position), BP and HR (sitting position), and collection of blood were obtained every 3h (8 readings/24h) from 19:00h to 16:00h the next day. Individual time series were analyzed for circadian characteristics by the least-squares fit of a 24& 12h cosine. After normalizing all data to percent of mean to reduce inter-subject variability in levels, grouped data were analyzed for time-effect by ANOVA and for circadian rhythm by multiple component (24h&12h) cosine fitting. Individual 24h averages were analyzed by simple and multiple regression for relationships between IOP and systemic variables, diabetic status and age.
  
  
  RESULTS
  Over the 34y study span, 22 men provided sixty-three 24h profiles for IOP & HR, 61 for BP, and 21 for NO. Using all normalized data, a significant circadian rhythm was found for each variable at p <0.001. Circadian peaks (orthophases) are located in the late morning for IOP-R (10:20h) and IOP-L (10:52h), and in the evening for HR (18:52h), NO (20:00h), SBP (20:40h) and DBP (21:44h). An out-of-phase relationship of about 10h is noted on a group basis between IOP vs BP, HR and NO. The locations of individual circadian peaks for IOP-R were found around the clock, but with a significant predominance between 10:00 and 16:00h (day type), and 04:00-10:00h (morning type). In contrast, BP, HR and NO showed a significant clustering of evening type or night type peaks. The overall mean IOP for the right eye was slightly, but not significantly, higher than the left eye (17.60+/-0.21 vs 17.34+/-0.18 mmHg; p = 0.385), with a strong positive correlation between both eyes (R = 0.952, p <0.0001). IOP showed a significant positive correlation with SBP (R = 0.49, p <0.001), diabetic status (R = 0.47, p <0.001), age (R = 0.32, p = 0.011), and HR (R = 0.28, p = 0.031). A multiple regression using SBP, DBP, HR, age and diabetic status (5 men became diabetic over the 34y study span) as independent variables resulted in SBP being the strongest predictor of IOP (p = 0.0001), followed by DBP (p = 0.0103). After adjustment for BP, independent effects of age (p = 0.187), HR (p = 0.789) and diabetic status (p = 0.153) were eliminated from the prediction equation.
  
  
  CONCLUSIONS
  The results of these studies reveal significant circadian variations in IOP, BP, HR and NO, with peak levels, on average, near noon for IOP and in the evening for BP, HR and NO. An increase in SBP was associated with an increase in IOP. While SBP and DBP are significant predictors of IOP levels, single measurements during regular clinic hours may not reveal the full functional relationship between the variables measured in our studies. Therefore, circadian information on total 24h patterns may contribute to the reliability of diagnosis and guide proper individualized timing of optimal patient management (e.g., for glaucoma, hypertension, diabetes, among other conditions).
authors.affiliation: Ophthalmology, Loyola University Med. Center, Maywood, IL, USA.
authors.forename: J I
authors.initials: JI
authors.lastname: Perlman
authors.forename: C M
authors.initials: CM
authors.lastname: Delany
authors.forename: R B
authors.initials: RB
authors.lastname: Sothern
authors.forename: K A
authors.initials: KA
authors.lastname: Skolnick
authors.forename: D
authors.initials: D
authors.lastname: Murray
authors.forename: R W
authors.initials: RW
authors.lastname: Jacobs
authors.forename: J L
authors.initials: JL
authors.lastname: Shue
authors.forename: E
authors.initials: E
authors.lastname: Kaplan
authors.forename: N C
authors.initials: NC
authors.lastname: Friedman
authors.forename: B A
authors.initials: BA
authors.lastname: Nemchausky
authors.forename: M D
authors.initials: MD
authors.lastname: Ryan
authors.forename: E L
authors.initials: EL
authors.lastname: Kanabrocki
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D000704:Analysis of Variance; D001794:Blood Pressure / Q000502:physiology*; D002909:Chronobiology Phenomena; D002940:Circadian Rhythm / Q000502:physiology*; D003920:Diabetes Mellitus; D005500:Follow-Up Studies; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D007429:Intraocular Pressure / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D009569:Nitric Oxide / Q000097:blood*; D011187:Posture; D012044:Regression Analysis; D012737:Sex Factors; D016683:Supine Position; D013997:Time Factors
chemical_list: D009569:Nitric Oxide