CDKN2B-AS1Genotype–Glaucoma Feature Correlations in Primary Open-Angle Glaucoma Patients From the United States




Purpose


To assess the association between single nucleotide polymorphisms (SNPs) of the gene region containing cyclin-dependent kinase inhibitor 2B antisense noncoding RNA ( CDKN2B-AS1 ) and glaucoma features among primary open-angle glaucoma (POAG) patients.


Design


Retrospective observational case series.


Methods


We studied associations between 10 CDKN2B-AS1 SNPs and glaucoma features among 976 POAG cases from the Glaucoma Genes and Environment (GLAUGEN) study and 1971 cases from the National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) consortium. For each patient, we chose the feature from the eye with the higher value. We created cohort-specific multivariable models for glaucoma features and then meta-analyzed the results.


Results


For 9 of the 10 protective CDKN2B-AS1 SNPs with minor alleles associated with reduced disease risk (eg, the G allele at rs2157719), POAG patients carrying these minor alleles had smaller cup-to-disc ratio (0.05 units smaller per G allele at diagnosis; 95% CI: −0.08, −0.03; P = 6.23E-05) despite having higher intraocular pressure (IOP) (0.70 mm Hg higher per G allele at DNA collection; 95% CI: 0.40, 1.00; P = 5.45E-06). For the 1 adverse rs3217992 SNP with minor allele A associated with increased disease risk, POAG patients with A alleles had larger cup-to-disc ratio (0.05 units larger per A allele at diagnosis; 95% CI: 0.02, 0.07; P = 4.74E-04) despite having lower IOP (−0.57 mm Hg per A allele at DNA collection; 95% CI: −0.84, −0.29; P = 6.55E-05).


Conclusion


Alleles of CDKN2B-AS1 SNPs, which influence risk of developing POAG, also modulate optic nerve degeneration among POAG patients, underscoring the role of CDKN2B-AS1 in POAG.


The cyclin-dependent kinase inhibitor 2B antisense noncoding RNA ( CDKN2B-AS1 ) genomic region on chromosome 9p21.3 is a genetic susceptibility locus for several age-related complex diseases (for an explanation of genetic terminology used in this manuscript see Table 1 ). Genome-wide association (GWA) studies and candidate gene investigations indicate that gene variants in this region are associated with primary open-angle glaucoma (POAG) but the relation between CDKN2B-AS1 genetic variants and specific glaucoma features is not well known. CDKN2B-AS1 is an antisense RNA that may influence the nearby CDKN2A (cyclin-dependent kinase inhibitor 2A) and CDKN2B (cyclin-dependent kinase inhibitor 2B) genes via regulatory mechanisms. CDKN2A and CDKN2B , which are expressed in all cell types, influence cell proliferation and senescence. Retinal ganglion cells (RGCs), a target for degeneration in POAG, must maintain a quiescent postmitotic state for an indefinite period in order to carry out their physiologic functions. In POAG, elevated intraocular pressure (IOP) and other insults may trigger quiescent RGCs to undergo apoptosis.



Table 1

Explanation of Genetic Terminology Used














































Term Definition
Allele One member of a DNA sequence pair that contributes to a trait. DNA sequence is comprised of a string of the following bases: adenine [A], guanine [G], cytosine [C], and thymine [T].
Antisense noncoding RNA A single-strand RNA that does not result in protein translation; rather, it can bind to nearby genes to alter their expression.
CDKN2BAS Cyclin-dependent kinase inhibitor 2B antisense RNA – a segment of DNA that generates noncoding RNA located near the CDKN2B gene on chromosome 9.
Eigenvector As it relates to an assessment of population structure, these are mathematically derived vectors representing a set of high-throughput genotypes into clusters that reflect ancestral tendencies.
Genotype Specifies the pair of alleles (1 paternal and 1 maternal) at any specific genomic location; for example, the following genotypes are possible at rs3217792 for CDKN2BAS : GG (wild-type), GA, AA (homozygous genotype for the minor variant).
Genome-wide association (GWA) study A study of the relation between a series of gene variants strategically located throughout the genome and a trait of interest (such as primary open-angle glaucoma).
Illumina Human660W-Quad-v1 array A type of commercially available chip that allows for genotyping at 660 000 locations throughout the human genome on a DNA sample.
Linkage disequilibrium block (LD block) A region in the genome where a set of SNPs is nonrandomly associated with each other. When the genotype of 1 SNP in an LD block is known, the genotypes of the other SNPs in the block can be predicted with reasonable accuracy.
METAL A contraction of met a a na l ysis; refers to a statistical software tool to synthesize large datasets such as high-throughout genotype data from various sources in a computer memory–efficient manner. For more information about METAL see www.sph.umich.edu/csg/abecasis/Metal/
Minor allele frequency (MAF)/minor allele Refers to the frequency of occurrence of the less common allele (aka the minor allele) when single nucleotide differences exist between members of the same species. For example, 2 individuals may contain the following sequence variants: CGAA C TA and CGAA T TA. The underlined nucleotide represents a single nucleotide polymorphic site and if T is less common and occurs 15% of the time, we say the MAF for T is 0.15.
PLINK An open-source analysis toolset used to analyze high-throughput genotyping data. For more information about PLINK see http://pngu.mgh.harvard.edu/~purcell/plink/
rs numbers (also known as ref SNP numbers) An assignment or address for a polymorphic site in the human genome. For example, rs3217792 resides in the CDKN2BAS region on chromosome 9p21. The major allele at this site is G, present in ∼63% of whites, and the minor allele at this site is A, present in 37% of whites.
SNP Single nucleotide polymorphism – a substitution of one allele for another in the genome; these substitutions can be common or rare and may or may not effect the function of the genomic segment in question. A common working hypothesis in genetic epidemiology research is that common SNPs serve as risk factors for complex diseases that are not inherited in a Mendelian fashion. Consider 3 unrelated individuals with a hypothetical stretch of DNA sequence:


  • –ATATCCG—



  • –ATATCCG—



  • G TATCCG—

The first base represents a polymorphic site or SNP in that the A allele is changed to a G allele for the third DNA sequence.


Sequence variants in CDKN2B-AS1 are associated with cup-to-disc ratio in a normal population. Interestingly, common minor alleles for several of these variants are associated with a smaller cup-to-disc ratio in normal subjects, as well as a reduced risk of POAG. Cup-to-disc ratio is a structural optic nerve feature highly correlated with the POAG disease process. POAG is a form of deleterious optic nerve aging without obvious secondary cause that is exacerbated by IOP and ultimately results in functional visual loss.


In this study we used the data from POAG cases enrolled in 2 large case-control groups where GWA studies have been completed: the GLAUGEN (Glaucoma Genes and Environment) study, part of the GENEVA (Gene, Environment Association Studies) consortium, and the NEIGHBOR (National Eye Institute Glaucoma Human Genetics Collaboration) consortium. In order to gain further insight regarding the CDKN2B-AS1 genomic region and the glaucomatous process, we assessed the association between 10 CDKN2B-AS1 single nucleotide polymorphisms (SNPs) strongly associated with POAG and glaucoma features like age at diagnosis, IOP parameters, cup-to-disc ratio, visual field parameters, and the need for laser trabeculoplasty (LTP) or incisional surgery.


Methods


Description of the Study Populations


The GLAUGEN study consists of POAG cases and controls drawn from the Nurses’ Health Study (NHS), the Health Professionals Follow-up Study (HPFS), and the Genetic Etiologies of Primary Open-Angle Glaucoma study (GEP). The former 2 studies are population-based, nested case-control studies and the latter study is a clinic-based case-control study from the Massachusetts Eye and Ear Infirmary (MEEI). Details regarding the inclusion/exclusion criteria for the GLAUGEN POAG case-control cohort have been described ( www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000308.v1.p1 ).


The NEIGHBOR consortium consists of POAG cases and controls from 12 sites. Details regarding the study sites, design, inclusion criteria, and clinical variables collected in the NEIGHBOR consortium have also been described elsewhere.


Case Definition


All cases had slit-lamp examinations, which did not reveal secondary cause of elevated IOP (such as exfoliation syndrome) and the anterior chamber angle was deemed nonoccludable. We did not employ IOP criteria in defining POAG. All cases had either reproducible visual field (VF) loss or 1 abnormal VF associated with cup-to-disc ratio >0.7 in the eye with loss. Reproducible VF loss consistent with nerve fiber layer pathology had to be demonstrated on tests that were considered reliable (fixation loss ≤33%, false-positive rate ≤20%, and false-negative rate ≤20%). We categorized the observed VF loss depending on whether it involved the paracentral zone, nasal step region, Bjerrum area, and the temporal wedge region above and/or below the horizontal meridian based on a systemic evaluation of the pattern deviation plot or its equivalent. There was no restriction placed on the type of VF perimeter used.


Genotyping Data


Details regarding DNA collection, extraction, and plating for GLAUGEN and NEIGHBOR have been previously described. We used the Illumina Human660W-Quad-v1 array (Illumina, San Diego, California, USA) for high-throughput genotyping. Both sets of genotyping data were subject to extensive quality control checks that have been previously described.


Gene Association Analyses and the 9p21 Polymorphisms Chosen for Analysis


After employing quality control filters, gene association analyses in GLAUGEN and NEIGHBOR were performed using PLINK v1.07. Details regarding these analyses have been described elsewhere. Briefly, in GLAUGEN among 976 cases and 1140 controls, no genetic loci achieved genome-wide significant association with POAG. In NEIGHBOR, among 2170 cases and 2347 controls, 17 SNPs reached genome-wide significance ( P ≤ 5E-08), 16 of which were in the CDKN2B-AS1 region. The top SNP associated with POAG was rs4977756 (odds ratio = 0.66; 95% CI: 0.59-0.73; P = 7.4E-16). Using METAL, we performed a meta-analysis of the GLAUGEN and NEIGHBOR dataset and identified 19 SNPs with genome-wide significant associations in relation to POAG, and 17 of these were in the CDKN2B-AS1 region. In this study of POAG phenotypes, we chose to analyze the top 10 CDKN2B-AS1 SNPs associated with POAG in the meta-analysis. The effect sizes, P values, and risk alleles for the chosen SNPs in relation to POAG are provided in the Supplemental Table (available at AJO.com ).


Ascertainment of Glaucoma Phenotype Features


We required that all cases included in our study have data on age at diagnosis ( Table 2 ). It can be difficult to ascertain age at diagnosis for POAG, as it is an insidious-onset disease; yet, the determination of whether CDKN2B-AS1 variants are associated with this glaucoma feature is important because an earlier age of diagnosis could translate into more visual disability from the condition later in life. Age at diagnosis in GLAUGEN and in NEIGHBOR was defined as the age at first sign of disease, namely, cup-to-disc ratio >0.6, cup-to-disc ratio asymmetry ≥0.2, IOP >21 mm Hg, or VF loss, which was ascertained based on medical record review.



Table 2

Demographic and Ocular Features of the Glaucoma Genes and Environment and National Eye Institute Glaucoma Human Genetics Collaboration Cases With Continuous Glaucoma Feature Variables a























































































Variable GLAUGEN NEIGHBOR
N Mean Min Max N Mean Min Max
Age at diagnosis (years) 976 63.6 40 87 1971 65.9 35 96
Intraocular pressure at diagnosis (mm Hg) b 345 23.7 12 45 n/a n/a n/a n/a
Intraocular pressure at DNA collection (mm Hg) b 469 16.0 10 41 1473 17.4 10 50
Cup-to-disc ratio at diagnosis b 458 0.62 0.01 0.95 n/a n/a n/a n/a
Cup-to-disc ratio at DNA collection b 485 0.80 0.2 0.99 1611 0.82 0.1 1
Pattern standard deviation (dB) b 802 5.88 1.00 16.46 1119 6.13 0.21 16.68
Mean defect (dB) b 849 −7.21 −33.22 1.64 1357 −9.52 −35.08 1.87

GLAUGEN = Glaucoma Genes and Environment; Max = maximum; Min = minimum; n/a = not available; NEIGHBOR = National Eye Institute Glaucoma Human Genetics Collaboration.

a Certain phenotype features were absent on some subsets of GLAUGEN and NEIGHBOR. For intraocular pressure (IOP) at diagnosis we included data from Nurses Health Study (NHS) and Health Professional Follow-up Study (HPFS) subset of GLAUGEN. For NEIGHBOR, data on IOP at diagnosis was available only for the Collaborative Initial Glaucoma Treatment Study subset of NEIGHBOR, and thus it was excluded. For IOP at DNA collection we included data from the Massachusetts Eye and Ear Infirmary (MEEI) subset of GLAUGEN and all NEIGHBOR subsites except for Johns Hopkins University and Collaborative Initial Glaucoma Treatment Study (CIGTS). For cup-to-disc ratio at diagnosis, data were available from NHS and HPFS only. For NEIGHBOR, data on cup-to-disc ratio at diagnosis were available only for the CIGTS subset of NEIGHBOR and thus it was excluded. For CDR at DNA collection we included data for the MEEI subset of GLAUGEN and all NEIGHBOR sites. Missing data for the visual field parameters reflects the fact that some participants had visual field tests other than Humphrey tests whereas others had advanced loss, creating spuriously low pattern standard deviation values.


b Maximum between the 2 eyes.



The IOP recorded was either at the time of diagnosis or at DNA collection (which was typically after diagnosis and while under treatment, especially for NEIGHBOR participants). We also recorded whether there was a history of IOP >21 mm Hg or the highest known IOP when such data were available. Similarly, cup-to-disc ratio recorded was either at diagnosis or at DNA collection. The type of IOP and cup-to-disc ratio data available varied by study subtype. Specifically, IOP and cup-to-disc ratio at diagnosis were available for NHS and HPFS cases in GLAUGEN. We excluded all NEIGHBOR cases from the assessment of CDKN2AB-AS1 SNPs in relation to IOP and cup-to-disc ratio at diagnosis as continuous variables because these features were available only in the Collaborative Initial Glaucoma Treatment Study ( www.clinicaltrials.gov ; NCT00000149 ) site. Nonetheless, a history of IOP ≥22 mm Hg at diagnosis was available on all NEIGHBOR participants. IOP and cup-to-disc ratio at DNA collection were available among MEEI cases in GLAUGEN and all NEIGHBOR cases except the Johns Hopkins University (JHU) and Collaborative Initial Glaucoma Treatment Study (CIGTS) sites. At the JHU site of NEIGHBOR, the collected IOPs represent the highest known values. For all study sites, the higher values between eyes were chosen for analysis. Box plots depicting the distribution of IOPs and cup-to-disc ratio by study site are provided in Supplemental Figures 1 and 2 (available at AJO.com ). Median IOP was >21 mm Hg in NHS, HPFS, CIGTS, the Advanced Glaucoma Intervention Study (AGIS; www.clinicaltrials.gov ; NCT00000148 ) site, and the JHU cases. For all other sites, the median IOP ranged between 15 and 18 mm Hg. Median cup-to-disc ratios ranged from 0.6-0.7 for sites with incident cases (NHS and HPFS in GLAUGEN and CIGTS in NEIGHBOR) and 0.8-0.9 across study centers with mostly prevalent cases (MEEI in GLAUGEN and West Virginia University, University of Pittsburgh, JHU, Stanford University, Duke University, University of Michigan, AGIS, and Marshfield Clinic in NEIGHBOR). Since age at diagnosis was unavailable at the University of Miami site, these cases were excluded from all CDKN2B-AS1 –glaucoma feature analyses.


For the VF global indices mean defect (MD) and pattern standard deviation (PSD), we chose the parameter from the eye showing more functional loss on the earliest available Humphrey VF test. A glaucoma specialist (L.R.P.) reviewed all VF tests and excluded cases judged to have nonglaucomatous loss (such as age-related macular degeneration) or lens rim artifact from CDKN2B-AS1 genotype–correlations analysis with MD, PSD, and pattern of VF loss. Furthermore, because PSD begins to decline with severe generalized reduction of retinal sensitivity, we excluded patients with MD values worse than −13 dB in the analysis of the relation between CDKN2B-AS1 SNPs and PSD (47 exclusions in GLAUGEN and 238 in NEIGHBOR). This cutoff was chosen based on inspection of a graph of MD vs PSD using the earliest available VF from NEIGHBOR and GLAUGEN participants (data not shown).


VFs were classified as having “peripheral VF loss only” if the paracentral zone was not involved. In contrast, VFs were categorized as having “paracentral VF loss only” if the nasal step regions, Bjerrum areas, and temporal wedge areas were not involved. Furthermore, VFs were classified as having “superior VF loss only” if the inferior hemifield of the pattern deviation plot was normal. The opposite was true for VF with “inferior VF loss only.” We also classified patients with “paracentral and peripheral loss” and patients with “superior and inferior loss.”


In GLAUGEN we collected data on a history of LTP and incisional glaucoma surgery of any kind. In NEIGHBOR these data were available only on the CIGTS and the AGIS sites. Since these procedures were performed as part of randomized clinical trials in CIGTS and AGIS, these data on laser and incisional surgery were excluded from genotype-phenotype correlations.


Statistical Analysis


We created multivariable linear regression models for continuous phenotypes and multiple logistic regression models for categorical phenotypes using SAS9.2 (SAS, Cary, North Carolina, USA). CDKN2B-AS1 SNPs were coded as minor allele dose variables with 3 values: 0 = no minor allele, 1 = 1 minor allele, and 2 = 2 minor alleles. We first analyzed the data from GLAUGEN and NEIGHBOR separately and performed tests for heterogeneity to check for appropriateness of pooling the results. When appropriate, we pooled the results using meta-analytic methods. We adjusted for variables that influenced genotyping call rates (which were all >98% in both studies): DNA source (blood or cheek), study site (NHS, HPFS, or GEP in GLAUGEN or the study subsite in NEIGHBOR), and the method of DNA extraction (GENTRA, DNAzol, or QIAGEN). We also adjusted the relation between genotypes and glaucoma features for population structure (a genetic surrogate of ancestry) using 3 eigenvectors in GLAUGEN and 2 eigenvectors in NEIGHBOR. Finally, we also adjusted for age at diagnosis (except when this was the outcome of interest) and sex in all models. We used the Bonferroni correction, accounting for the number of unique linkage disequilibrium (LD) blocks where our SNPs were located (5 blocks; Supplemental Figure 3 , available at AJO.com ) and the number of unique glaucoma features we assessed as outcomes (10), to establish P values <.001 as statistically significant.


In secondary analyses assessing the association of CDKN2B-AS1 SNPs with cup-to-disc ratio parameters, we additionally controlled for atonal homolog 7 ( ATOH7 ) SNPs (rs7916697 and rs3858145) strongly correlated with disc area. For associations between CDKN2B-AS1 SNPs that showed statistically significant associations with VF parameters, we further adjusted for cup-to-disc ratio. Finally, since age at diagnosis can depend on IOP level but IOP criteria were not employed in diagnosing glaucoma, we performed a secondary analysis of the relation between CDKN2B-AS1 and age at diagnosis among cases with no history of IOP ≥22 mm Hg.




Results


The 976 GLAUGEN patients and 1971 NEIGHBOR patients for whom we recorded the age at diagnosis represents 100% (976/976) and 90.8% (1971/2170) of the POAG cases, respectively, that completed high-throughput genotyping in these cohorts. Tables 2 and 3 summarize the demographic and ocular features for POAG cases. The mean age at diagnosis was slightly less in GLAUGEN than in NEIGHBOR. The minimal age at diagnosis in these studies corresponds to the minimal age criteria for inclusion in the respective studies. As expected, mean IOP at diagnosis was higher than the mean IOP at DNA collection because the former represented untreated levels ( Table 2 ). Similarly, the cup-to-disc ratio at diagnosis was smaller than the cup-to-disc ratio at DNA collection because the latter came from prevalent cases. While VF loss was required for all cases, MD values were available for only 87% (849/976) and 69% (1357/1971) of GLAUGEN and NEIGHBOR cases, respectively, because not all subjects had Humphrey VFs. Table 3 also shows the percentage of patients with the various types of VF loss patterns.



Table 3

Demographic and Ocular Features of Glaucoma Genes and Environment and National Eye Institute Glaucoma Human Genetics Collaboration Cases With Binary Glaucoma Feature Variables a







































































































Variable GLAUGEN NEIGHBOR
% > Cutoff N % > Cutoff N
Age at diagnosis ≥65 years 49.3 976 56.5 1971
Sex (% female) 58.4 976 52.1 1971
Intraocular pressure ≥22 mm Hg at diagnosis 67.0 976 79.4 1219
Cup-to-disc ratio ≥0.6 at diagnosis 69.9 458 n/a n/a
Cup-to-disc ratio ≥0.6 at DNA collection 96.3 485 95.8 1611
Laser trabeculoplasty 28.2 976 36.8 38
Incisional glaucoma surgery 15.1 976 55.0 40
Pattern standard deviation ≥6 decibels 39.8 802 45.4 1119
Mean defect ≤−13 decibels 14.6 849 26.6 1357
Peripheral visual field loss only b 52.1 963 31.5 1423
Paracentral visual field loss only b 17.9 963 3.0 1423
Both peripheral and paracentral visual field loss b 30.0 963 65.1 1423
Superior visual field loss only b 38.8 963 27.6 1423
Inferior visual field loss only b 30.3 963 21.2 1423
Both superior and inferior visual field loss b 28.8 963 50.7 1423

GLAUGEN = Glaucoma Genes and Environment; Max = maximum; Min = minimum; n/a = not available; NEIGHBOR = National Eye Institute Glaucoma Human Genetics Collaboration.

a Certain phenotype features were absent on some subsets of GLAUGEN and NEIGHBOR. We included data on CDR >0.6 at diagnosis from the Nurses Health Study (NHS) and Health Professionals Follow-up Study (HPFS) subsets of GLAUGEN. We included data on CDR >0.6 at DNA collection from the Massachusetts Eye and Ear Infirmary (MEEI) subset of GLAUGEN and all NEIGHBOR sites. For laser trabeculoplasty and incisional glaucoma surgery we included data from GLAUGEN as well as the Collaborative Initial Glaucoma Treatment Study and Advanced Glaucoma Intervention Study subsites of NEIGHBOR. Missing data for the visual field parameters ( mean defects and pattern standard deviation ) solely reflects the fact that some participants had visual field tests other than Humphrey tests. Missing data for parameters related to the pattern of visual loss (eg, peripheral visual field loss only ) occurred for several reasons, including that visual field loss was confounded from deficits not attributable to glaucoma, like age-related macula degeneration, or that tests assessed segments outside the range of the central 24 or 30 degrees.


b These visual field loss attributes are applied on a per-patient basis. For instance, peripheral visual field loss only means that 1 or both eyes of a patient have peripheral visual field loss and neither has paracentral field loss.



The LD block structure for the CDKN2B-AS1 SNPs is provided in Supplemental Figure 3 . The minor allele for the most upstream SNP (rs32177992) is associated with increased POAG risk; the remainder are associated with decreased POAG risk.


Table 4 provides data for the associations between each minor allele for CDKN2B-AS1 SNPs and continuous glaucoma features after meta-analysis of the GLAUGEN and NEIGHBOR data. Table 5 shows the associations between each minor allele for the CDKN2B-AS1 SNPs and dichotomous glaucoma features determined by meta-analysis.



Table 4

Multivariable Difference (95% Confidence Intervals, P Value) for Continuous Glaucoma Feature Associated With Each Increase in Minor Allele of Cyclin-Dependent Kinase Inhibitor 2B Antisense Noncoding RNA ( CDKN2BAS ) Single Nucleotide Polymorphisms























































































































































































LD Block 1 LD Block 2 LD Block 3 LD Block 4 LD Block 5
rs3217992 rs1063192 rs573687 rs7049105 rs2157719 rs2151280 rs1412829 rs1012068 rs4977756 rs1412832
Age at diagnosis (y) −0.20 (−0.73, 0.34) 0.76 (−0.20, 1.72) 1.00 (0.02, 1.98) 0.24 (−0.30, 0.77) 0.64 (−0.38, 1.66) 0.20 (−0.33, 0.74) 0.73 (−0.12, 1.58) 0.42 (−0.13, 0.96) 0.67 (−0.15, 1.48) 0.65 (−0.07, 1.37)
P = .47 P = .12 P = .05 P = .39 P = .22 P = .45 P = .09 P = .13 P = .11 P = .08
IOP at diagnosis (mm Hg) −0.65 (−1.38, 0.09) 0.68 (−0.06, 1.42) 0.97 (0.20, 1.74) 0.68 (−0.05, 1.41) 0.74 (0.00, 1.49) 0.73 (0.02, 1.45) 0.73 (−0.01, 1.48) 0.69 (−0.04, 1.41) 0.72 (−0.06, 1.50) 0.64 (−0.21, 1.50)
P = .08 P = .07 P = .01 P = .07 P = .05 P = .05 P = .05 P = .06 P = .07 P = .14
IOP at DNA collection (mm Hg) −0.57 (−0.84, −0.29) 0.62 (0.32, 0.92) 0.62 (0.30, 0.94) 0.59 (0.31, 0.87) 0.70 (0.40, 1.00) 0.60 (0.32, 0.88) 0.65 (0.35, 0.95) 0.59 (0.31, 0.88) 0.70 (0.39, 1.01) 0.77 (0.43, 1.10)
P = 6.55E-05 P = 4.67E-05 P = 1.43E-04 P = 4.14E-05 P = 5.45E-06 P = 2.55E-05 P = 2.46E-05 P = 4.31E-05 P = 8.75E-06 P = 8.26E-06
CDR at diagnosis 0.05 (0.02, 0.07) −0.05 (−0.08, −0.03) −0.06 (−0.09, −0.03) −0.05 (−0.07, −0.02) −0.05 (−0.08, −0.03) −0.05 (−0.07, −0.03) −0.05 (−0.08, −0.03) −0.05 (−0.07, −0.02) −0.06 (−0.09, −0.03) −0.06 (−0.09, −0.03)
P = 4.74E-04 P = 1.25E-04 P = 1.74E-05 P = 1.96E-04 P = 6.23E-05 P = 8.14E-05 P = 1.32E-04 P = 1.16E-04 P = 7.58E-06 P = 2.12E-05
CDR at DNA collection 0.01 (0.00, 0.01) −0.02 (−0.04, 0.00) −0.01 (−0.02, 0.00) −0.01 (−0.02, 0.00) −0.01 (−0.03, 0.00) −0.01 (−0.02, 0.00) −0.02 (−0.03, 0.00) −0.01 (−0.01, 0.00) −0.01 (−0.03, 0.01) −0.01 (−0.02, 0.00)
P = .09 P = .12 P = .10 P = .03 P = .14 P = .08 P = .12 P = .07 P = .16 P = .08
PSD (dB) 0.50 (0.30, 0.71) −0.30 (−0.52, −0.09) −0.19 (−0.42, 0.04) −0.35 (−0.55, −0.14) −0.31 (−0.54, −0.09) −0.36 (−0.56, −0.15) −0.31 (−0.53, −0.09) −0.36 (−0.57, −0.16) −0.34 (−0.56, −0.11) −0.30 (−0.55, −0.06)
P = 1.50E-06 P = .01 P = .11 P = 9.00E-04 P = .01 P = 6.00E-04 P = .01 P = 6.00E-04 P = .004 P = .02
MD (dB) −0.45 (−0.83, −0.07) 0.34 (−0.22, 0.90) 0.39 (−0.22, 1.00) 0.31 (−0.07, 0.69) 0.32 (−0.09, 0.73) 0.31 (−0.06, 0.69) 0.41 (0.00, 0.82) 0.32 (−0.06, 0.71) 0.26 (−0.24, 0.75) 0.16 (−0.36, 0.68)
P = .02 P = .23 P = .22 P = .11 P = .12 P = .10 P = .05 P = .10 P = .31 P = .54

CDR = cup-to-disc ratio; IOP = intraocular pressure; LD = linkage disequilibrium; MD = mean defect; PSD = pattern standard deviation; y = years.

Significance and effect sizes of associations of CDKN2BAS region SNPs after meta-analysis of Glaucoma Genes and Environment (GLAUGEN) and National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) cases using linear regression on various outcome variables. Significant P values are in bold. We used a Bonferroni corrected statistical significance level of 0.001 (0.05/[( 5 representative SNPs) x (10 outcome variables)]). No models had a P for heterogeneity <.05. GLAUGEN regression models controlled for age of diagnosis, DNA specimen source (blood or cheek), sex, site, method of DNA extraction, and 3 eigenvectors. NEIGHBOR regression models controlled for age of diagnosis, DNA specimen source (blood or cheek), sex, site, and 2 eigenvectors.

NB: Certain phenotype features were absent on some subsets of GLAUGEN and NEIGHBOR. For IOP at diagnosis we included data from Nurses Health Study (NHS) and Health Professional Follow-up Study (HPFS) subset of GLAUGEN. For NEIGHBOR, data on IOP at diagnosis were available only for the Collaborative Initial Glaucoma Treatment Study (CIGTS) subset of NEIGHBOR and thus it was excluded. For IOP at DNA collection we included data from Massachusetts Eye and Ear Infirmary (MEEI) subset of GLAUGEN and all NEIGHBOR subsites except for Johns Hopkins University and CIGTS. For CDR at diagnosis, data were available from NHS and HPFS only. For NEIGHBOR, data on CDR at diagnosis were available only for the CIGTS subset of NEIGHBOR and thus it was excluded. For CDR at DNA collection we included data for the MEEI subset of GLAUGEN and all NEIGHBOR sites.


Table 5

Multivariable Odds Ratio (95% Confidence Intervals, P Value) for Dichotomous Glaucoma-Related Variables Associated With Each Increase in Minor Allele of Cyclin-Dependent Kinase Inhibitor 2B Antisense Noncoding RNA ( CDKN2BAS ) Single Nucleotide Polymorphisms














































































































































































































LD Block 1 LD Block 2 LD Block 3 LD Block 4 LD Block 5
rs3217992 rs1063192 rs573687 rs7049105 rs2157719 rs2151280 rs1412829 rs1012068 rs4977756 rs1412832
History of IOP >21 mm Hg 0.72 (0.58, 0.90) 1.39 (1.17, 1.66) 1.48 (1.26, 1.74) 1.38 (1.08, 1.77) 1.48 (1.19, 1.83) 1.40 (1.10, 1.78) 1.44 (1.19, 1.73) 1.38 (1.08, 1.76) 1.39 (1.04, 1.84) 1.36 (1.06, 1.76)
P = .004 P = 2.00E-04 P = 2.12E-06 P = .01 P = 4.00E-04 P = .01 P = 2.00E-04 P = .01 P = .02 P = .02
CDR >0.6 at diagnosis 1.44 (1.07, 1.94) 0.71 (0.53, 0.95) 0.68 (0.50, 0.92) 0.74 (0.56, 0.98) 0.71 (0.53, 0.95) 0.72 (0.54, 0.95) 0.71 (0.53, 0.96) 0.71 (0.54, 0.94) 0.63 (0.47, 0.86) 0.65 (0.48, 0.90)
P = .02 P = .02 P = .01 P = .04 P = .02 P = .02 P = .02 P = .02 P = .003 P = .01
CDR>0.6 at DNA collection 1.43 (1.04, 1.97) 0.71 (0.52, 0.98) 0.81 (0.58, 1.13) 0.68 (0.50, 0.92) 0.73 (0.53, 1.00) 0.68 (0.50, 0.92) 0.74 (0.54, 1.01) 0.75 (0.55, 1.02) 0.68 (0.49, 0.94) 0.75 (0.53, 1.05)
P = .03 P = .03 P = .22 P = .01 P = .05 P = .01 P = .06 P = .06 P = .02 P = .09
Filtration surgery 1.14 (0.88, 1.46) 0.91 (0.69, 1.19) 1.02 (0.77, 1.36) 0.80 (0.62, 1.03) 0.90 (0.68, 1.18) 0.82 (0.64, 1.06) 0.93 (0.71, 1.23) 0.85 (0.66, 1.11) 0.91 (0.69, 1.21) 0.75 (0.55, 1.04)
P = .33 P = .48 P = .88 P = .09 P = .44 P = .13 P = .62 P = .23 P = .54 P = .09
Peripheral only visual field loss 0.79 (0.70, 0.89) 1.23 (1.09, 1.40) 1.15 (1.01, 1.31) 1.21 (1.01, 1.45) 1.24 (1.09, 1.41) 1.22 (1.03, 1.45) 1.23 (1.08, 1.40) 1.19 (0.94, 1.50) 1.17 (1.03, 1.34) 1.19 (1.03, 1.37)
P = 1.00E-04 P = .002 P = .04 P = .04 P = 9.00E-04 P = .02 P = .002 P = .14 P = .02 P = .02
Paracentral only visual field loss 0.91 (0.73, 1.13) 0.97 (0.76, 1.23) 1.13 (0.80, 1.60) 1.12 (0.9, 1.39) 1.01 (0.77, 1.32) 1.11 (0.90, 1.38) 1.00 (0.80, 1.25) 1.14 (0.92, 1.41) 1.03 (0.82, 1.29) 1.00 (0.62, 1.61)
P = .39 P = .79 P = .48 P = .29 P = .94 P = .31 P = .99 P = .22 P = .80 P = .99
Superior only visual field loss 1.03 (0.89, 1.20) 0.9 (0.79, 1.03) 0.96 (0.84, 1.11) 0.93 (0.74, 1.18) 0.90 (0.79, 1.03) 0.95 (0.77, 1.18) 0.92 (0.81, 1.05) 0.95 (0.8, 1.12) 0.91 (0.80, 1.05) 0.88 (0.76, 1.02)
P = .71 P = .12 P = .60 P = .58 P = .14 P = .67 P = .23 P = .53 P = .20 P = .10
Inferior only visual field loss 0.87 (0.76, 0.99) 1.23 (1.07, 1.42) 1.19 (1.03, 1.37) 1.17 (1.02, 1.35) 1.23 (1.07, 1.42) 1.14 (1.00, 1.30) 1.2 (1.04, 1.38) 1.12 (0.98, 1.28) 1.19 (1.04, 1.38) 1.15 (0.99, 1.35)
P = .03 P = .003 P = .02 P = .02 P = .004 P = .05 P = .01 P = .09 P = .02 P = .07

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Jan 9, 2017 | Posted by in OPHTHALMOLOGY | Comments Off on CDKN2B-AS1Genotype–Glaucoma Feature Correlations in Primary Open-Angle Glaucoma Patients From the United States

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