August 2007
Volume 48, Issue 8
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Glaucoma  |   August 2007
Genetic Contributions to Glaucoma: Heritability of Intraocular Pressure, Retinal Nerve Fiber Layer Thickness, and Optic Disc Morphology
Author Affiliations
  • Leonieke M. E. van Koolwijk
    From the Glaucoma Service, The Rotterdam Eye Hospital, Rotterdam, The Netherlands; the
    Departments of Epidemiology and Biostatistics and
    Clinical Genetics, Genetic Epidemiology Unit, Erasmus Medical Center, Rotterdam, The Netherlands; and the
  • Dominiek D. G. Despriet
    Department of Ophthalmology and the
    Departments of Epidemiology and Biostatistics and
    Clinical Genetics, Genetic Epidemiology Unit, Erasmus Medical Center, Rotterdam, The Netherlands; and the
    Department of Molecular and Clinical Ophthalmogenetics, The Netherlands Institute for Neuroscience, Amsterdam, The Netherlands.
  • Cornelia M. van Duijn
    Departments of Epidemiology and Biostatistics and
    Clinical Genetics, Genetic Epidemiology Unit, Erasmus Medical Center, Rotterdam, The Netherlands; and the
  • Luba M. Pardo Cortes
    Departments of Epidemiology and Biostatistics and
    Clinical Genetics, Genetic Epidemiology Unit, Erasmus Medical Center, Rotterdam, The Netherlands; and the
  • Johannes R. Vingerling
    Department of Ophthalmology and the
  • Yurii S. Aulchenko
    Departments of Epidemiology and Biostatistics and
    Clinical Genetics, Genetic Epidemiology Unit, Erasmus Medical Center, Rotterdam, The Netherlands; and the
  • Ben A. Oostra
    Departments of Epidemiology and Biostatistics and
    Clinical Genetics, Genetic Epidemiology Unit, Erasmus Medical Center, Rotterdam, The Netherlands; and the
  • Caroline C. W. Klaver
    Department of Ophthalmology and the
    Departments of Epidemiology and Biostatistics and
    Clinical Genetics, Genetic Epidemiology Unit, Erasmus Medical Center, Rotterdam, The Netherlands; and the
    Department of Molecular and Clinical Ophthalmogenetics, The Netherlands Institute for Neuroscience, Amsterdam, The Netherlands.
  • Hans G. Lemij
    From the Glaucoma Service, The Rotterdam Eye Hospital, Rotterdam, The Netherlands; the
Investigative Ophthalmology & Visual Science August 2007, Vol.48, 3669-3676. doi:10.1167/iovs.06-1519
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      Leonieke M. E. van Koolwijk, Dominiek D. G. Despriet, Cornelia M. van Duijn, Luba M. Pardo Cortes, Johannes R. Vingerling, Yurii S. Aulchenko, Ben A. Oostra, Caroline C. W. Klaver, Hans G. Lemij; Genetic Contributions to Glaucoma: Heritability of Intraocular Pressure, Retinal Nerve Fiber Layer Thickness, and Optic Disc Morphology. Invest. Ophthalmol. Vis. Sci. 2007;48(8):3669-3676. doi: 10.1167/iovs.06-1519.

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      © 2016 Association for Research in Vision and Ophthalmology.

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Abstract

purpose. The genetic etiology of primary open-angle glaucoma (POAG) is still largely unknown, because of its complexity and disparities in its classification. This study was undertaken to determine the genetic contribution to various early, continuous markers of POAG by assessing the heritability of intraocular pressure (IOP), retinal nerve fiber layer (RNFL) thickness, and neuroretinal rim and optic disc parameters in a genetically isolated population.

methods. A total of 2620 subjects (mean age, 48 years; range 18–86) from extended pedigrees living in a small town in The Netherlands underwent an extensive ophthalmic examination. Their IOP was measured by Goldmann applanation tonometry, their RNFL thickness by scanning laser polarimetry (GDx VCC), and their optic disc parameters by confocal scanning laser ophthalmoscopy (HRT II). Risk associations were explored by linear regression analyses and heritability estimates by variance component methods.

results. Inbreeding was present in 2042 (81%) participants, and was significantly associated with a higher IOP (P < 0.001). The heritability estimate for IOP was 0.35 (95% confidence interval [CI], 0.27–0.43); for RNFL thickness, 0.48 (95% CI, 0.35–0.60); and for neuroretinal rim area, 0.39 (95% CI, 0.20–0.58). Nongenetic factors accounted for only a small proportion (≤0.13) of the variance in all three traits.

conclusions. Early, continuous markers of POAG are strongly determined by additive genetic effects. The results support a quantitative trait linkage strategy to discover new genes for POAG.

Primary open-angle glaucoma (POAG) is the second leading cause of blindness worldwide. 1 The sharp rise in the ageing population will probably cause a 30% increase in the number of patients with POAG by 2020, with an estimate of 58.6 million affected and 5.9 million bilaterally blind. 2 Established risk factors for POAG are age, race, intraocular pressure (IOP), central corneal thickness (CCT), high myopia, and a positive family history. 3 4 Dissection of the genetic background has resulted in an association with 20 genetic loci and three genes: MYOC, OPTN, WDR36. 5 6 7 In addition, genes causing congenital glaucoma or glaucoma-associated developmental syndromes may contribute to adult-onset POAG. Some (e.g., CYP1B1) are already recognized to be involved, the role of others (PITX2, FOXC1, PAX6, and LMX1B) remains to be fully assessed in adult cases. 8 9 10 11 12 13 The currently identified genes probably contribute to the pathogenesis of POAG in <5% of cases in the general population. 14 15 16 17 18 19 Hence, genes that explain a more significant fraction of POAG remain to be identified. 
Gene-finding in POAG has been hampered by etiological and clinical heterogeneity, partly due to nonuniformity of diagnostic criteria. Its insidious onset and slow natural course impede a definite diagnosis at an early stage, whereas including only late-stage, outright POAG will greatly limit genetic studies because relatively few people would be available to participate. These difficulties fuel the question of whether studying heritable, continuous markers of POAG may improve the chance of success in gene finding. 
Quantitative markers of POAG, apart from IOP, are retinal nerve fiber layer (RNFL) thickness and optic disc rim area, both indicators of the number of existing retinal ganglion cells, or indirectly, of any of their loss, typical of glaucoma. 20 21 22 Previous studies, mostly performed in twins or nuclear families, reported heritability estimates for IOP ranging from 0.29 to 0.50 and for cup-to-disc ratio ranging from 0.48 to 0.80. 23 24 25 26 The ranges of these heritability estimates are relatively large, and studies based on more extended pedigrees may provide more precise figures. 
We performed a family-based cohort study in a genetically isolated population in The Netherlands and thereby had the opportunity to study large extended pedigrees. As a first investigation into the genetic etiology of early markers of POAG, we explored the heritability estimates for IOP, RNFL thickness, and optic disc rim area. We used the imaging techniques scanning laser polarimetry (SLP) and confocal scanning laser ophthalmoscopy (CSLO) to obtain objective measurements. This study also allowed us to demonstrate the effect of inbreeding and nongenetic factors on these POAG markers. 
Methods
Subjects
Subjects were recruited as part of the Erasmus Rucphen Family (ERF) study. This family-based cohort study was designed to identify susceptibility genes for various complex disorders by studying quantitative traits. The ERF study is being conducted in a genetically isolated population located in the southwest of The Netherlands. This population was founded in the middle of the 18th century by a limited number of individuals (<400), and was characterized by rapid growth and little immigration until the past few decades. The genealogical database, which contains information on the current inhabitants of this area and their ancestors, includes more than 80,000 records. Genetic characterization of this population has been presented elsewhere. 27 28 29 The research adhered to the tenets of the Declaration of Helsinki and was approved by the Medical Ethics Committee of Erasmus Medical Center in Rotterdam. Informed consent was obtained after explanation of the nature and possible consequences of the study. 
Eligibility for participation in the study was determined by genealogical background, not by any phenotypes of interest. Twenty-two families were selected who had at least six children baptized in the community church between 1880 and 1900. All living descendants of these families aged 18 years and older, as well as their spouses, were invited to attend a series of clinical examinations. A total of 2620 subjects underwent ophthalmic examination. 
Based on genotyping half of the sample (n = 1430, 437 nuclear families with one or both tested parents and one or more tested offspring) with 5964 single nucleotide polymorphisms (SNPs), we identified only one nuclear family in which the father was not compatible with any of the three offspring (whereas the siblings were compatible with each other). Exclusion of this family did not alter the heritability estimates. As the percentage of nonpaternities is low and is known for only half the sample, the presence of nonpaternities was ignored in the data presented. 
Clinical Examination
All data were collected between June 2002 and February 2005. Nonophthalmic examinations included anthropometric measurements, cardiovascular and endocrine assessments, neuropsychological tests, fasting blood samples, and interviews regarding medical history, medication, and putative risk factors. 
The ophthalmic examination comprised the assessment of best-corrected visual acuity, refraction, and IOP. Keratometry was determined by an automatic refractometer, and the eyes’ axial lengths by an intraocular lens calculator (IOL Master; Carl Zeiss Meditec, Inc., Dublin, CA). Scanning laser polarimetry (SLP) was subsequently performed with the commercially available GDx VCC (Carl Zeiss Meditec, Inc.). In mydriasis, participants underwent fundus photography centered on the optic disc (20°, TRC-50XT retinal camera; Topcon Medical Systems, Inc., Paramus, NJ) and confocal scanning laser ophthalmoscopy (CSLO) measurements (Heidelberg Retina Tomograph II; [HRT II] Heidelberg Engineering GmbH, Dossenheim, Germany). 
Intraocular Pressure
One of five trained examiners performed bilateral IOP measurements with Goldmann applanation tonometry. A drop of fluorescein sodium was instilled in each eye. The tonometer was set at 10, and the prism was carefully applied to the corneal surface of the right eye. Without looking at the scale, the examiner rotated the dial until the inner margins of the two semicircles touched each other. The examiner then moved the slit lamp away from the eye and read the IOP. The tonometer was set at 10, and the measurement was repeated. If the two measurements differed, a third measurement was performed, and the median value was recorded. The procedure was repeated for the left eye. 
RNFL Thickness
After any refractive error was entered into the GDx VCC software, the birefringence of the anterior segment of each participant was assessed by means of the method described by Zhou and Weinreb. 30 Subsequently, each eye was scanned with adjusted anterior segment compensation to estimate peripapillary RNFL thickness as described by Reus and Lemij. 31 The cutoff for the quality of the image was a GDx VCC scan quality score of 8 or above. Images with lower scores were excluded. 
After the boundaries of the optic disc were manually marked, the GDx VCC software positioned two circles centered on the disc: The first had a diameter of ∼2.5 mm (54 pixels), the second a diameter of ∼3.3 mm (70 pixels). The parameters of RNFL thickness that we used in this study were based on the RNFL thickness measurements between the circles: TSNIT average (temporal-superior-nasal-inferior-temporal), superior average (25°–144°), inferior average (215°–334°), and the worst hemifield average (the lowest average value of the RNFL thickness of the hemifields of both eyes). 
Neuroretinal Rim
Details of the CSLO technique have been described elsewhere. 32 Briefly, imaging was performed after entering the participant’s keratometry data into the software and after adjusting the settings in accordance with the refractive error. Only images with a standard deviation of height measurements below 50 μm were accepted. The optic disc margin was manually marked at the inner edge of Elschnig’s ring by one observer (LMEvK). The HRT II software then calculated stereometric parameters of the optic disc and neuroretinal rim. The parameters that we used were disc area, rim area, rim area superotemporally (45°–90°), rim area inferotemporally (270°–315°), rim-to-disc area ratio, vertical cup-to-disc ratio, and cup shape measure, an index of depth variation and steepness of the cup walls. 
Statistical Analysis
The inbreeding coefficient, which represents the probability that the two alleles at a given locus are identical by descent (i.e., derived from the same ancestral chromosome), was calculated, based on all available genealogical information, by means of PEDIG software. 33 This coefficient was analyzed in quartiles, since its distribution was skewed toward zero. 
Other putative covariates of glaucoma pathogenesis that were studied included age, sex, height, body mass index, systolic blood pressure, pulse rate, fasting blood glucose level, blood cholesterol level, IOP, time of IOP measurement, axial length of the eye, spherical equivalent of refractive error, and mean corneal curvature. The glaucoma markers that were studied were IOP, TSNIT average, superior average, inferior average, worst hemifield average, disc area, rim area, superotemporal rim area, inferotemporal rim area, rim-to-disc area ratio, vertical cup-to-disc ratio, and cup shape measure. These markers were based on the eye most representative of glaucoma: the eye with the lower RNFL thickness parameters, rim area parameters, and rim-to-disc area ratio and the eye with the higher IOP, vertical cup-to-disc ratio, and cup shape measurement. We calculated the mean of both eyes for the analyses of disc area. If a measurement could be obtained in only one eye, the parameters of this eye were included in the analyses. 
Associations were explored by univariate and multivariate linear regression (SPSS version 11.0 for Windows; SPSS, Chicago, IL). All determinants below the 0.10 significance level in the multivariate analyses were retained in the final model for heritability estimation. The distribution of the multivariate regression residuals in the final model was tested for normality with the nonparametric, one-sample Kolmogorov-Smirnov test. To reduce kurtosis of the distribution in parameters describing RNFL thickness or rim area, we excluded the upper and lower 0.5 percentile values of these traits. We further transformed traits that were skewed using natural logarithm (disc area, rim area), or exponential function (vertical cup-to-disc ratio). 
We estimated the heritability by means of a variance component maximum likelihood analysis, as implemented in Solar software (ver. 2.1.2). 34 35 A variance component analysis separates the observed phenotypic variance into components that are attributable to different causes. Heritability describes the relative importance of the component that is attributable to heredity. This component is called the additive genetic variance and represents the cumulative effects of alleles. Heritability can be estimated from the resemblance between family members. We first examined the proportion of the phenotypic variance associated with the covariates. Subsequently, we estimated the proportion of the remaining phenotypic variance explained by additive genetic effects. Finally, the heritability of each glaucoma marker was calculated as the proportion of the total phenotypic variance explained by additive genetic effects. In addition, we investigated the genetic correlation between rim area and disc area with a linear bivariate analysis. 
Results
Demographic and clinical characteristics of the study population are presented in Table 1 . The population was almost all Caucasian, and ages ranged from 18 to 86 years. 
A total of 2042 (81%) participants had an inbreeding coefficient greater than zero, indicating at least some degree of inbreeding. The median inbreeding coefficient was 0.00187, and 186 (7.4%) participants had an inbreeding coefficient of at least 0.016, indicating that their parents were second cousins or closer relatives. 
Intraocular Pressure
Tonometry was successfully performed in 2457 (93.8%) subjects. Twenty-three subjects (0.9%) received IOP-lowering therapy or had a history of these medications and were excluded from the IOP analyses. 
IOP values of the right and the left eye were significantly correlated (Pearson correlation coefficient 0.855; P < 0.001). IOP was significantly higher in the right eye than in the left eye (paired samples t-test; mean difference 0.10 mm Hg; 95% CI, 0.03–0.16). 
Data have been presented for the eye with the higher IOP. The distribution of the IOP in the study population is given in Table 2 , and the results of the linear regression and variance component analyses are in Table 3 . Age, inbreeding, and fasting glucose were significantly associated with IOP, and corneal curvature was inversely related. These covariates accounted for 0.05 of the total phenotypic variance of IOP. Of the remaining variance, the proportion explained by additive genetic effects was 0.37 (95% CI, 0.29–0.45). The heritability estimate, calculated as the contribution of genetic factors to the total phenotypic variance, was 0.35 (95% CI, 0.27–0.43). 
RNFL Thickness
Only 1552 (59% of total) subjects underwent RNFL thickness measurements, because this procedure was introduced after the study had commenced. Twenty-one (1.4%) subjects were excluded due to poor quality of the images. 
The distributions of the RNFL thickness parameters are presented in Table 2 . The nerve fiber indicator (NFI) was ≥40 (i.e., suggestive of glaucoma) in 20 (1.8%) of 1085 subjects younger than 55 years, and 41 (9.2%) of 446 subjects 55 years of age or older. 
The results of the linear regression and variance component analyses are reported in Table 4 . Inbreeding and IOP were not significantly related to any RNFL thickness parameter. Age and systolic blood pressure were inversely associated with all parameters, although the relation between systolic blood pressure and inferior average did not reach statistical significance (P = 0.144). Axial length, spherical equivalent, and corneal curvature, all of which are covariates of refractive error, were significantly associated with most RNFL thickness parameters. 
The proportion of the total phenotypic variance of RNFL thickness explained by the determinants in Table 4ranged from 0.03 (inferior average) to 0.07 (superior average). Of the remaining variance, the proportion explained by additive genetic effects was 0.50 (95% CI, 0.36–0.63) for TSNIT average, 0.43 (95% CI, 0.31–0.56) for superior average, 0.50 (95% CI, 0.37–0.63) for inferior average, and 0.49 (95% CI, 0.37–0.60) for worst hemifield average. The heritability estimates for all parameters of RNFL thickness were significant, and ranged from 0.40 (95% CI, 0.29–0.52) for superior average to 0.49 (95% CI, 0.36–0.61) for inferior average. 
Neuroretinal Rim and Optic Disc Morphology
Data of the first 750 participants were included in this analysis. Of these, eight (1.1%) subjects were excluded because of poor quality of the topographic images. 
The distributions of all optic disc parameters that were measured have been presented in Table 2 . The Moorfields regression classification was outside normal limits in 13 (2.8%) of 458 subjects less than 55 years of age, and 29 (10.2%) of 284 subjects more than 55 years of age. 
Table 5shows the results of the linear regression and variance component analyses. Inbreeding and IOP were not associated with any optic disc parameter. Age showed a statistically significant association with disc area, rim-to-disc area ratio, and vertical cup-to-disc ratio. Determinants of refractive error (axial length, spherical equivalent, and corneal curvature) were significantly related to most parameters. 
These covariates explained a fraction of 0.13 of the variance in disc area, 0.02 to 0.06 of the variance in rim area parameters, and 0.06 of the variance in cup shape measure. Of the remaining variance, additive genetic effects accounted for 0.59 (95% CI, 0.42–0.77) of disc area, 0.41 (95% CI, 0.21–0.61) to 0.84 (95% CI, 0.69–0.98) of rim area parameters, and 0.42 (95% CI, 0.21–0.63) of cup shape measure. This resulted in heritability estimates of 0.52 (95% CI, 0.36–0.67) for disc area, 0.39 (95% CI, 0.20–0.58) to 0.79 (95% CI, 0.65–0.93) for rim area parameters, and 0.40 (95% CI, 0.20–0.59) for cup shape measure. 
We analyzed coaggregation of rim and disc area and found a low genetic correlation (r genetic = 0.16; SE = 0.13, P = 0.26). 
Discussion
This study was performed to assess the heritability of early, continuous POAG markers in a large family-based cohort study by using objective imaging techniques. IOP, RNFL thickness, and neuroretinal rim area were strongly genetically determined, with heritability estimates of 0.35, 0.48, and 0.39, respectively. Nongenetic factors, although significantly associated with glaucoma phenotypes, were responsible for only a small proportion of the variance of these traits. 
The design of our study had several limitations. First, genetically isolated populations may exhibit genetic drift, and their genetic composition may therefore deviate from the general population. We performed simulation studies in the ERF population, which showed that the effects of genetic drift on the frequency of common alleles were negligible. 28 Thus, we believe it is valid to generalize our results to an outbred population. A second limitation is that we studied a relatively young and healthy cohort, which may reduce the clinical relevance of our findings. This problem appeared to be small, since the proportion of subjects aged 60+ years was considerable (20%), and the range of outcome variables was representative of the clinical spectrum. Third, measurements of RNFL thickness and neuroretinal rim area were for logistic reasons not performed on the total study population. We do not think that this affected the outcome of our results, because the subsets were chosen randomly and had sufficient statistical power. Fourth, we did not have the opportunity to study central corneal thickness (CCT), a potential confounder of IOP measurements as well as an important risk factor for POAG. 36 37 CCT has previously been reported to account for between 1% and 6% of the total variance in IOP measured with Goldmann applanation tonometry. 38 39 40 41 The heritability of CCT has been estimated to be 0.95. 42 Because we did not include CCT into the variance component analysis of IOP, CCT-determining genes may have been incorrectly considered to be IOP-determining genes, thus inflating our heritability estimate of IOP. 
RNFL thickness and optic disc morphology were not associated with IOP in these relatively young individuals not suspected of having glaucoma. An elevated IOP has been recognized as an important risk factor for glaucoma. 37 43 IOP levels have been shown to correlate with optic disc characteristics in eyes of subjects with ocular hypertension. 44 This may suggest that IOP affects the RNFL and optic disc pathophysiologically rather than physiologically. The results of Chang et al. 25 support this hypothesis. Other studies, however, reported a significant effect of IOP on optic disc morphology in normal subjects. 45 46  
How do our findings relate to other studies of POAG heritability? Our estimate of 0.35 for IOP is remarkably similar to that in the two most recent studies of the heritability of IOP. Klein et al. 24 estimated a heritability of 0.35 from the parent–child correlation in the Beaver Dam Eye Study. Chang et al. 25 reported a heritability estimate of 0.36 in a population-based cohort of Caucasian sibships 65 to 84 years of age. The heritability estimate of RNFL thickness in our study (0.48) was much lower than the estimate reported by Hougaard et al. 47 (0.78–0.82), who studied monozygotic and dizygotic twins. Heritability may be population specific. Even populations with similar genetic backgrounds may show different heritability estimates due to different environmental variances and different study designs. Heritability studies based on twins assume that the environmental correlations among monozygotic and dizygotic twins are equal. However, if this “equal environment assumption” does not hold, the heritability estimated from twin data alone may be higher than that derived from extended families, as in our study. 48 Different measurement methods (OCT in Hougaard et al. 47 versus GDx VCC in our study) and different adjustments for covariates may also contribute to the heritability differences. There are no former studies that assessed the heritability of optic disc rim area, but three studies estimated the heritability of cup-to-disc ratio as a proxy. Our estimate for this parameter of 0.64 was in their reported range of 0.48–0.80. 24 25 26  
We were able to study optic disc morphology objectively with the HRT II, a technique that had not been used before in heritability studies. We found heritabilities of 0.52 for disc area, 0.39 for total rim area, and 0.47 for inferotemporal rim area. We found a markedly higher estimate (0.79) for the rim-to-disc ratio, indicating a larger genetic contribution for the combination than for any of the parameters separately. Speculating that different sets of genes may determine rim and disc area, we performed a bivariate analysis of these parameters and found no evidence of any genetic correlation. 
As a general rule, inbreeding increases the probability that the gene profile comprises two identical alleles. In our study, inbreeding was significantly associated with a higher IOP, suggesting the presence of causative recessive alleles in the genetic background of this trait. Evidence from previous studies supports this notion. Recessive mutations in the CYP1B1 gene not only link to congenital glaucoma and anterior segment dysgenesis, but also play a role in high-pressure POAG with juvenile or adult onset. 8 9 Inbreeding was not associated with RNFL thickness or neuroretinal rim area. Therefore, our study does not support a recessive inheritance of these POAG markers. 
In conclusion, we have demonstrated that IOP, RNFL thickness, and neuroretinal rim area are continuous POAG markers that are strongly determined by genetic effects. Genome-wide association methods have been successfully applied to map genes for other complex disorders. A quantitative trait analysis greatly enhances the statistical power of this technology. The high heritabilities that we found in the current study encourage us to use this approach for identifying new POAG genes. 
 
Table 1.
 
Characteristics of the Study Population
Table 1.
 
Characteristics of the Study Population
Characteristic
Age, mean (y) ± SD 47.98 ± 14.26
 <55 y (%) 65.4
 55+ y (%) 34.6
Male gender (%) 44.1
Inbreeding >0 (%) 81.1
Inbreeding coefficient, median (range) 0.00187 (0.00000–0.06286)
Height men, mean (cm) ± SD 174.72 ± 7.21
Height women, mean (cm) ± SD 161.82 ± 6.51
Body mass index men, mean (kg/m2) ± SD 27.27 ± 4.18
Body mass index women, mean (kg/m2) ± SD 26.51 ± 4.96
Systolic blood pressure, mean (mm Hg) ± SD 139.54 ± 20.16
Pulse rate, mean (bpm) ± SD 70.49 ± 12.21
Fasting blood glucose, mean (mM) ± SD 4.58 ± 0.99
Length of eye axis, mean (mm) ± SD 23.22 ± 1.05
Spherical equivalent, mean (D) ± SD 0.04 ± 1.93
High myopia (≤−6 D) (%) 1.4
Corneal curvature, mean (mm) ± SD 7.71 ± 0.26
Table 2.
 
Distribution of IOP, RNFL Thickness, and Optic Disc Morphology
Table 2.
 
Distribution of IOP, RNFL Thickness, and Optic Disc Morphology
Age Category <55 y (n = 1596) Age Category 55+ y (n = 838)
IOP, mean (mm Hg) ± SD 15.27 ± 3.05 15.98 ± 2.79
IOP ≥22 mm Hg (%) 0.9 1.6
RNFL thickness n = 1085 n = 446
 TSNIT average, mean (μm) ± SD 57.18 ± 5.92 55.00 ± 5.97
 Superior average, mean (μm) ± SD 68.82 ± 7.71 64.13 ± 8.59
 Inferior average, mean (μm) ± SD 64.12 ± 8.62 61.19 ± 7.82
 Worse hemifield average, mean (μm) ± SD 63.08 ± 7.96 59.68 ± 7.69
Optic disc morphology n = 458 n = 284
 Disc area, mean (mm2) ± SD 1.86 ± 0.34 1.89 ± 0.36
 Rim area, mean (mm2) ± SD 1.36 ± 0.23 1.35 ± 0.27
 Rim area sup-temp, mean (mm2) ± SD 0.16 ± 0.04 0.16 ± 0.04
 Rim area inf-temp, mean (mm2) ± SD 0.18 ± 0.04 0.17 ± 0.05
 Rim-disc area ratio, mean ± SD 0.76 ± 0.12 0.73 ± 0.15
 Vertical cup-disc ratio, mean ± SD 0.37 ± 0.20 0.40 ± 0.24
 Cup shape measure, mean ± SD −0.16 ± 0.06 −0.14 ± 0.06
Table 3.
 
Linear Regression and Variance Component Analyses of Intraocular Pressure
Table 3.
 
Linear Regression and Variance Component Analyses of Intraocular Pressure
Determinants Regression Coefficient (SE) P Proportion Explained by Determinants Proportion Explained by Additive Genetic Effects
Of Remaining Variance Of Total Variance
IOP Age 0.025 (0.004); P < 0.001 0.050 0.368 (0.042) P < 0.001 0.350 (0.040) P < 0.001
Male gender 0.147 (0.128); P = 0.246
Inbreeding 0.201 (0.061); P < 0.001
Pulse rate 0.009 (0.005); P = 0.069
Fasting glucose 0.262 (0.065); P < 0.001
Corneal curvature −0.869 (0.245); P < 0.001
Table 4.
 
Linear Regression and Variance Component Analyses of RNFL Thickness
Table 4.
 
Linear Regression and Variance Component Analyses of RNFL Thickness
Determinants Regression Coefficient (SE) P Proportion Explained by Determinants Proportion Explained by Additive Genetic Effects
Of Remaining Variance Of Total Variance
TSNIT average Age −0.055 (0.013); P < 0.001 0.038 0.495 (0.067) P < 0.001 0.476 (0.064) P < 0.001
Male gender −0.337 (0.321); P = 0.294
Inbreeding −0.116 (0.149); P = 0.435
BMI 0.084 (0.036); P = 0.021
SBP −0.020 (0.009); P = 0.033
Axial length 0.664 (0.212); P = 0.002
Spherical equivalent 0.241 (0.118); P = 0.040
Superior average Age −0.108 (0.016); P < 0.001 0.070 0.432 (0.063) P < 0.001 0.402 (0.058); P < 0.001
Male gender −0.257 (0.412); P = 0.529
BMI 0.103 (0.048); P = 0.034
SBP −0.028 (0.013); P = 0.030
Fasting glucose −0.364 (0.239); P = 0.129
Corneal curvature 3.702 (0.796); P < 0.001
Inferior average Age −0.074 (0.018); P < 0.001 0.033 0.503 (0.067) P < 0.001 0.487 (0.064) P < 0.001
Male gender −0.729 (0.458); P = 0.112
SBP −0.019 (0.013); P = 0.144
Axial length 0.987 (0.300); P < 0.001
Spherical equivalent 0.194 (0.166); P = 0.242
Worst hemifield average Age −0.088 (0.016); P < 0.001 0.060 0.485 (0.061) P < 0.001 0.456 (0.057) P < 0.001
Male gender −0.165 (0.400); P = 0.682
BMI 0.083 (0.047); P = 0.077
SBP −0.031 (0.012); P = 0.011
Fasting glucose −0.294 (0.234); P = 0.208
Corneal curvature 3.131 (0.777); P < 0.001
Table 5.
 
Linear Regression and Variance Component Analyses of Optic Disc Morphology
Table 5.
 
Linear Regression and Variance Component Analyses of Optic Disc Morphology
Determinants Regression Coefficient (SE) P Proportion Explained by Determinants Proportion Explained by Additive Genetic Effects
Of Remaining Variance Of Total Variance
Disc area Age 0.016 (0.006); P = 0.008 0.130 0.593 (0.089) P < 0.001 0.516 (0.078) P < 0.001
Male gender 0.480 (0.196); P = 0.014
Inbreeding 0.106 (0.074); P = 0.153
Height −0.011 (0.011); P = 0.317
SBP 0.006 (0.003); P = 0.097
Axial length −0.405 (0.119); P < 0.001
Spherical equivalent −0.317 (0.059); P < 0.001
Corneal curvature 2.819 (0.373); P < 0.001
Rim area Age 0.039 (0.028); P = 0.162 0.037 0.407 (0.102) P < 0.001 0.392 (0.098) P < 0.001
Male gender 1.886 (0.665); P = 0.005
Inbreeding 0.088 (0.357); P = 0.801
SBP −0.019 (0.018); P = 0.276
Axial length −1.487 (0.565); P = 0.009
Spherical equivalent −0.986 (0.281); P < 0.001
Corneal curvature 5.541 (1.793); P = 0.002
Rim area superior-temporal Age 0.003 (0.006); P = 0.617 0.025 0.426 (0.095) P < 0.001 0.415 (0.093) P < 0.001
Male gender −0.059 (0.218); P = 0.787
Height 0.023 (0.013); P = 0.066
Axial length −0.198 (0.093); P = 0.034
Spherical equivalent −0.184 (0.051); P < 0.001
Rim area inferior-temporal Age −0.003 (0.007); P = 0.667 0.020 0.483 (0.097) P < 0.001 0.473 (0.095) P < 0.001
Male gender 0.155 (0.161); P = 0.332
Inbreeding 0.066 (0.088); P = 0.453
SBP −0.004 (0.004); P = 0.363
Axial length −0.244 (0.138); P = 0.077
Spherical equivalent −0.179 (0.068); P = 0.009
Corneal curvature 0.770 (0.436); P = 0.077
Rim-disc area ratio Age −0.010 (0.004); P = 0.024 0.055 0.835 (0.075) P < 0.001 0.789 (0.071) P < 0.001
Male gender 0.006 (0.145); P = 0.968
Height 0.010 (0.009); P = 0.250
SBP −0.004 (0.003); P = 0.089
Spherical equivalent 0.042 (0.026); P = 0.110
Corneal curvature −1.001 (0.194); P < 0.001
Vertical cup-disc ratio Age 0.017 (0.004); P < 0.001 0.058 0.684 (0.089) P < 0.001 0.645 (0.084) P < 0.001
Male gender −0.054 (0.088); P = 0.535
SBP 0.004 (0.002); P = 0.085
Spherical equivalent −0.065 (0.024); P = 0.007
Corneal curvature 0.883 (0.181); P < 0.001
Cup shape measure Age 0.018 (0.011); P = 0.089 0.060 0.420 (0.105) P < 0.001 0.395 (0.099) P < 0.001
Male gender 0.568 (0.360); P = 0.114
Height −0.067 (0.020); P < 0.001
BMI −0.056 (0.028); P = 0.043
SBP 0.012 (0.006); P = 0.074
Fasting glucose 0.213 (0.146); P = 0.144
Axial length 0.390 (0.117); P < 0.001
The authors thank all participants in the ERF study and Hans Bij de Vaate, Patricia van Hilten, Margot Walter, Lidian van Amsterdam, Riet Bernaerts, Leon Testers, and all research assistants for help in data collection; and Petra Veraart and Hilda Kornman for genealogical research. 
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Table 1.
 
Characteristics of the Study Population
Table 1.
 
Characteristics of the Study Population
Characteristic
Age, mean (y) ± SD 47.98 ± 14.26
 <55 y (%) 65.4
 55+ y (%) 34.6
Male gender (%) 44.1
Inbreeding >0 (%) 81.1
Inbreeding coefficient, median (range) 0.00187 (0.00000–0.06286)
Height men, mean (cm) ± SD 174.72 ± 7.21
Height women, mean (cm) ± SD 161.82 ± 6.51
Body mass index men, mean (kg/m2) ± SD 27.27 ± 4.18
Body mass index women, mean (kg/m2) ± SD 26.51 ± 4.96
Systolic blood pressure, mean (mm Hg) ± SD 139.54 ± 20.16
Pulse rate, mean (bpm) ± SD 70.49 ± 12.21
Fasting blood glucose, mean (mM) ± SD 4.58 ± 0.99
Length of eye axis, mean (mm) ± SD 23.22 ± 1.05
Spherical equivalent, mean (D) ± SD 0.04 ± 1.93
High myopia (≤−6 D) (%) 1.4
Corneal curvature, mean (mm) ± SD 7.71 ± 0.26
Table 2.
 
Distribution of IOP, RNFL Thickness, and Optic Disc Morphology
Table 2.
 
Distribution of IOP, RNFL Thickness, and Optic Disc Morphology
Age Category <55 y (n = 1596) Age Category 55+ y (n = 838)
IOP, mean (mm Hg) ± SD 15.27 ± 3.05 15.98 ± 2.79
IOP ≥22 mm Hg (%) 0.9 1.6
RNFL thickness n = 1085 n = 446
 TSNIT average, mean (μm) ± SD 57.18 ± 5.92 55.00 ± 5.97
 Superior average, mean (μm) ± SD 68.82 ± 7.71 64.13 ± 8.59
 Inferior average, mean (μm) ± SD 64.12 ± 8.62 61.19 ± 7.82
 Worse hemifield average, mean (μm) ± SD 63.08 ± 7.96 59.68 ± 7.69
Optic disc morphology n = 458 n = 284
 Disc area, mean (mm2) ± SD 1.86 ± 0.34 1.89 ± 0.36
 Rim area, mean (mm2) ± SD 1.36 ± 0.23 1.35 ± 0.27
 Rim area sup-temp, mean (mm2) ± SD 0.16 ± 0.04 0.16 ± 0.04
 Rim area inf-temp, mean (mm2) ± SD 0.18 ± 0.04 0.17 ± 0.05
 Rim-disc area ratio, mean ± SD 0.76 ± 0.12 0.73 ± 0.15
 Vertical cup-disc ratio, mean ± SD 0.37 ± 0.20 0.40 ± 0.24
 Cup shape measure, mean ± SD −0.16 ± 0.06 −0.14 ± 0.06
Table 3.
 
Linear Regression and Variance Component Analyses of Intraocular Pressure
Table 3.
 
Linear Regression and Variance Component Analyses of Intraocular Pressure
Determinants Regression Coefficient (SE) P Proportion Explained by Determinants Proportion Explained by Additive Genetic Effects
Of Remaining Variance Of Total Variance
IOP Age 0.025 (0.004); P < 0.001 0.050 0.368 (0.042) P < 0.001 0.350 (0.040) P < 0.001
Male gender 0.147 (0.128); P = 0.246
Inbreeding 0.201 (0.061); P < 0.001
Pulse rate 0.009 (0.005); P = 0.069
Fasting glucose 0.262 (0.065); P < 0.001
Corneal curvature −0.869 (0.245); P < 0.001
Table 4.
 
Linear Regression and Variance Component Analyses of RNFL Thickness
Table 4.
 
Linear Regression and Variance Component Analyses of RNFL Thickness
Determinants Regression Coefficient (SE) P Proportion Explained by Determinants Proportion Explained by Additive Genetic Effects
Of Remaining Variance Of Total Variance
TSNIT average Age −0.055 (0.013); P < 0.001 0.038 0.495 (0.067) P < 0.001 0.476 (0.064) P < 0.001
Male gender −0.337 (0.321); P = 0.294
Inbreeding −0.116 (0.149); P = 0.435
BMI 0.084 (0.036); P = 0.021
SBP −0.020 (0.009); P = 0.033
Axial length 0.664 (0.212); P = 0.002
Spherical equivalent 0.241 (0.118); P = 0.040
Superior average Age −0.108 (0.016); P < 0.001 0.070 0.432 (0.063) P < 0.001 0.402 (0.058); P < 0.001
Male gender −0.257 (0.412); P = 0.529
BMI 0.103 (0.048); P = 0.034
SBP −0.028 (0.013); P = 0.030
Fasting glucose −0.364 (0.239); P = 0.129
Corneal curvature 3.702 (0.796); P < 0.001
Inferior average Age −0.074 (0.018); P < 0.001 0.033 0.503 (0.067) P < 0.001 0.487 (0.064) P < 0.001
Male gender −0.729 (0.458); P = 0.112
SBP −0.019 (0.013); P = 0.144
Axial length 0.987 (0.300); P < 0.001
Spherical equivalent 0.194 (0.166); P = 0.242
Worst hemifield average Age −0.088 (0.016); P < 0.001 0.060 0.485 (0.061) P < 0.001 0.456 (0.057) P < 0.001
Male gender −0.165 (0.400); P = 0.682
BMI 0.083 (0.047); P = 0.077
SBP −0.031 (0.012); P = 0.011
Fasting glucose −0.294 (0.234); P = 0.208
Corneal curvature 3.131 (0.777); P < 0.001
Table 5.
 
Linear Regression and Variance Component Analyses of Optic Disc Morphology
Table 5.
 
Linear Regression and Variance Component Analyses of Optic Disc Morphology
Determinants Regression Coefficient (SE) P Proportion Explained by Determinants Proportion Explained by Additive Genetic Effects
Of Remaining Variance Of Total Variance
Disc area Age 0.016 (0.006); P = 0.008 0.130 0.593 (0.089) P < 0.001 0.516 (0.078) P < 0.001
Male gender 0.480 (0.196); P = 0.014
Inbreeding 0.106 (0.074); P = 0.153
Height −0.011 (0.011); P = 0.317
SBP 0.006 (0.003); P = 0.097
Axial length −0.405 (0.119); P < 0.001
Spherical equivalent −0.317 (0.059); P < 0.001
Corneal curvature 2.819 (0.373); P < 0.001
Rim area Age 0.039 (0.028); P = 0.162 0.037 0.407 (0.102) P < 0.001 0.392 (0.098) P < 0.001
Male gender 1.886 (0.665); P = 0.005
Inbreeding 0.088 (0.357); P = 0.801
SBP −0.019 (0.018); P = 0.276
Axial length −1.487 (0.565); P = 0.009
Spherical equivalent −0.986 (0.281); P < 0.001
Corneal curvature 5.541 (1.793); P = 0.002
Rim area superior-temporal Age 0.003 (0.006); P = 0.617 0.025 0.426 (0.095) P < 0.001 0.415 (0.093) P < 0.001
Male gender −0.059 (0.218); P = 0.787
Height 0.023 (0.013); P = 0.066
Axial length −0.198 (0.093); P = 0.034
Spherical equivalent −0.184 (0.051); P < 0.001
Rim area inferior-temporal Age −0.003 (0.007); P = 0.667 0.020 0.483 (0.097) P < 0.001 0.473 (0.095) P < 0.001
Male gender 0.155 (0.161); P = 0.332
Inbreeding 0.066 (0.088); P = 0.453
SBP −0.004 (0.004); P = 0.363
Axial length −0.244 (0.138); P = 0.077
Spherical equivalent −0.179 (0.068); P = 0.009
Corneal curvature 0.770 (0.436); P = 0.077
Rim-disc area ratio Age −0.010 (0.004); P = 0.024 0.055 0.835 (0.075) P < 0.001 0.789 (0.071) P < 0.001
Male gender 0.006 (0.145); P = 0.968
Height 0.010 (0.009); P = 0.250
SBP −0.004 (0.003); P = 0.089
Spherical equivalent 0.042 (0.026); P = 0.110
Corneal curvature −1.001 (0.194); P < 0.001
Vertical cup-disc ratio Age 0.017 (0.004); P < 0.001 0.058 0.684 (0.089) P < 0.001 0.645 (0.084) P < 0.001
Male gender −0.054 (0.088); P = 0.535
SBP 0.004 (0.002); P = 0.085
Spherical equivalent −0.065 (0.024); P = 0.007
Corneal curvature 0.883 (0.181); P < 0.001
Cup shape measure Age 0.018 (0.011); P = 0.089 0.060 0.420 (0.105) P < 0.001 0.395 (0.099) P < 0.001
Male gender 0.568 (0.360); P = 0.114
Height −0.067 (0.020); P < 0.001
BMI −0.056 (0.028); P = 0.043
SBP 0.012 (0.006); P = 0.074
Fasting glucose 0.213 (0.146); P = 0.144
Axial length 0.390 (0.117); P < 0.001
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