Abstract
Purpose
To determine the relationship between positive family history (FH) and primary open-angle glaucoma (POAG) diagnosis and clinical presentation in the Primary Open-Angle African American Glaucoma Genetics (POAAGG) cohort.
Methods
FH of POAG in first-degree relatives was assessed in 2365 subjects in the POAAGG cohort. A standardized interview was used to assess FH of glaucoma, demographic characteristics, lifestyle choices, and medical and ocular comorbidities.
Results
Positive FH was associated with increased risk of POAG (age-adjusted odds ratio and 95% confidence interval 3.4[2.8, 4.1]). In age-adjusted analysis among POAG cases, positive FH was associated with younger age (P<0.001), female gender (P<.001), hypertension (P=.006), use of hypertension medication (P=.03), and prior glaucoma surgery (P=.02). Cases with positive FH also had thicker retinal nerve fiber layers (P=.03).
Conclusions
The risk conferred by positive FH suggests strong genetic underpinnings for some patients with this disease, which will be investigated by genome-wide association studies and whole exome sequencing.
Keywords: Glaucoma, Primary Open-Angle Glaucoma, African American, African American Recruitment, Family History, Retinal Nerve Fiber Layer, Intraocular pressure
INTRODUCTION
Primary open-angle glaucoma (POAG) is the leading cause of irreversible blindness worldwide, affecting approximately 70 million people.1 Multiple epidemiological studies have confirmed that Africans Americans are disproportionately affected by POAG and present earlier2,3 with more severe4–6 and rapidly progressive disease.4,7,8 African Americans with glaucoma also face more adverse outcomes, such as worse visual fields and optic disc cupping,9,10 blindness,11,12 decreased vision-related quality of life,13,14 and increased mortality.15,16
Positive family history (FH) strongly correlates with POAG risk in African Americans,17 reflecting heritability and/or shared environmental factors. Studies in Nigeria,18 Barbados,19 Congo,20 and Baltimore17 found that individuals of African descent with positive FH of glaucoma had up to an 18-fold higher risk of developing the disease.20 The Baltimore Eye Survey and the Barbados Eye Study found that siblings of affected patients are at greatest risk of developing POAG, compared to parents or children.17,19 Patients report maternal FH more often than paternal FH,21,22 which may reflect knowledge bias. The increased risk conveyed by both positive FH and African descent calls for a closer analysis of this group’s disease origins and presentation.
The Primary Open-Angle African American Glaucoma Genetics (POAAGG) study cohort is the largest African American POAG cohort recruited to date. This study was designed to elucidate the genetic architecture of POAG in African Americans. The objective of this report was to assess the relationship between positive FH and POAG diagnosis in this overaffected population.
METHODS
STUDY DESIGN
The POAAGG study is a five year population-based project funded by the National Eye Institute of the National Institutes of Health. The study population consists of self-identified blacks (African Americans, African descent, or African Caribbean) 35 years or older, identified from the Scheie Eye Institute at the University of Pennsylvania (UPenn) and its research affiliates in Philadelphia. Participants were recruited for the POAAGG study from July 2010 with UPenn institutional review board (IRB) approval. The study design, along with the baseline demographics and socioeconomic background of this population, have been reported elsewhere.23
ASCERTAINMENT, ELIGIBILITY, AND PHENOTYPING
Certified clinical research coordinators screened potential subjects based on IRB-approved inclusion/exclusion criteria23 and approached eligible patients during regularly scheduled appointments to Department of Ophthalmology physicians.24 Subjects provided a signed informed consent and genomic DNA, which was extracted from peripheral blood or saliva. All enrolled patients underwent a full onsite exam, which included: (1) verification of name, age at enrollment, date of birth, street address, gender, and informed consent with signature (2) completion of a questionnaire in-clinic; (3) evaluation of height and weight; (4) explanation of procedure for blood or saliva collection for DNA analysis; (5) Visual Acuity (VA) measured using Snellen chart at 20 feet; (6) automated refraction with a Reichert Phoropter RS Automatic Refractor (Reichert Technologies, Depew, NY) if the presented VA was not 20/20 in either eye, followed by manual refraction; (7) near vision assessed using the Snellen chart at near with the participant’s present reading prescription; (8) intraocular pressure (IOP) measured with a Goldmann applanation tonometer; (9) anterior and posterior segment examinations by slit lamp with a 90-diopter lens for optic nerve examination and indirect ophthalmoscopy; (10) gonioscopy confirming the presence of an Open-Angle; (11) central corneal thickness and axial length measurements assessed with an ultrasonic A-scan/pachymeter DGH 4000B SBH IOL Computation module (DGH Tech Inc., Exton, PA); (12) visual field test utilizing the Humphrey Automated Field Analyzer (Standard 24-2 Swedish interactive thresholding algorithm); (13) stereo disc photos and fundus photography utilizing the Topcon TRC 50EX Retinal Camera (Topcon Corp. of America, Paramus, NJ); (14) Optical coherence topography (OCT) using either Cirrus or Stratus OCT (Carl Zeiss Meditec, Dublin, CA). The outcomes of the procedures and all diagnoses were discussed with the patient at the conclusion of the examination.
Fellowship-trained glaucoma specialists defined cases and controls based on the following criteria. POAG cases were defined as having an open iridocorneal angle and: (1) characteristic glaucomatous optic nerve findings in one or both eyes consisting of at least one of the following: notching, neuroretinal rim thinning, excavation, or a nerve fiber layer defect; (2) characteristic visual field defects in at least one eye detected on two consecutive reliable visual field tests and consistent with observed optic nerve defects in that same eye, as determined by fellowship-trained glaucoma specialists; and (3) all secondary causes of glaucoma excluded. Normal controls were defined as subjects older than 35, without any of the following: (1) high myopia (greater than −8.00 diopters); (2) high hyperopia (+8.00 diopters); (3) abnormal visual field; (4) IOP greater than 21 mmHg; (5) neuroretinal rim thinning, excavation, notching or nerve fiber layer defects; (6) optic nerve asymmetry; or (7) a cup to disc ratio difference between eyes greater than 0.2. A preliminary masked concordance study among glaucoma specialists at three institutions found a 97% concordance rate in diagnosis of 120 glaucoma cases and controls.23
Subjects were excluded from the analysis if they had withdrawn from the study or had disease status as glaucoma suspect. The suspects often represent potential glaucoma patients who do not yet meet the inclusion criteria of characteristic and corresponding visual field defects on two consecutive visual fields, as the second visual field test is scheduled in the future. Also excluded were patients with self-report of unknown FH of glaucoma or lack of recorded FH information.
DATA COLLECTION
During the enrollment process, subjects were asked a series of standardized, detailed questions about FH of glaucoma.
Over the course of the POAAGG study, the research team transitioned from the use of a case-report form (CRF) to the electronic database REDCap (Research Electronic Data Capture). From July 2010 to November 2012, FH data was recorded in the CRFs. Patients were asked in an interview to report a positive, negative, or unknown FH of glaucoma in their first-degree relatives, as well as the name and relationship to the subject of each affected family member. With the introduction of REDCap in November 2012, additional questions were added to obtain a more detailed FH of glaucoma. These questions included positive, negative, or unknown history of glaucoma in first degree relatives (children, siblings, parents) and second degree relatives (parent’s siblings, grandparents).
To supplement CRF data after transitioning to REDCap, electronic medical records (EMRs) were reviewed for all subjects enrolled prior to November 2012. These records were used to update the database with answers to the new questions added during the transition to REDCap. If detailed FH data was not available in the EMRs, patients were then recontacted for more detailed FH information.
All ocular characteristics obtained during the onsite exam (described above) were stored in REDCap. This study specifically examined VA, cup-to-disc ratio (CDR), max IOP, central corneal thickness (CCT), retinal nerve fiber layer (RNFL), and mean deviation (MD) in cases. For max IOP, cut-off ranges of <21, 21-30, and >30 mmHg were used, as 21 mmHg is the arbitrary cut-off for POAG screening worldwide and 30 mmHg is correlated with considerable increase in POAG prevalence.25 RNFL thickness cut-off ranges of <60, 60-80, and >80 μm were used because a value <60 μm typically implies glaucoma/glaucoma suspect, while 70-79 μm is considered suspicious and >80 μm is characteristic of normal non-glaucomatous eyes.26
CROSS-CHECKING OF FH DATA
To verify FH data across sources, a random sample of 200 subjects (97 cases and 103 controls) were drawn. For each patient, glaucoma FH in the REDCap database was compared to glaucoma FH reported in either CRFs or EMRs (Epic at UPenn).
In REDCap, positive FH in any relatives was present in 90 subjects, absent in 101 subjects, and unknown in 9 subjects (Supplementary Table 1). FH data in REDCap had an 83.5% agreement with Epic and CRFs (weighted Kappa and 95% confidence interval 0.7[0.6, 0.8]). Specifically, 81 (90%) of 90 patients had positive FH in REDCap that was verifiable in Epic or CRFs, and 83 (82%) of 101 subjects had negative FH in REDCap that was verifiable in Epic or CRFs. FH records had an 89.7% concordance rate (0.8[0.7–0.9]) among POAG cases and 77.7% concordance rate (0.6[0.5–0.7]) among controls.
STATISTICAL ANALYSIS
This analysis was performed on a total of 2365 subjects (1041 controls and 1324 cases), who were enrolled as of Year 5 of study initiation. We assessed the association of FH of glaucoma with POAG diagnosis using odds ratios and their 95% confidence intervals from univariate and age-adjusted logistic regression models. Patient and ocular characteristics were compared between POAG cases with versus without FH of glaucoma using generalized linear models with and without age-adjustment. In the comparison of ocular characteristics, the inter-eye correlation was accounted for by using the generalized estimating equations. All the statistical comparisons were performed in SAS v9.4 (SAS Institute Inc, Cary, NC), and two-sided P<0.05 was considered statistically significant.
RESULTS
DEMOGRAPHICS
Cases were an average of 10 years older than controls, with mean ages (± standard deviation) of 70.9 ± 11.3 and 61.1 ± 11.7, respectively (Table 1). Approximately two-thirds of cases and controls were female (61% and 68%, respectively).
Table 1.
Characteristics of African American Cases and Controls in the Study Cohort.
| Characteristic | Level | Controls n=1041 (44%) |
Cases n=1324 (56%) |
|---|---|---|---|
| Age | <50 | 202 (19.4%) | 46 (3.5%) |
| 50-59 | 283 (27.2%) | 197 (14.9%) | |
| 60-69 | 306 (29.4%) | 350 (26.4%) | |
| 70-79 | 192 (18.4%) | 422 (31.9%) | |
| >=80 | 58 (5.6%) | 309 (23.3%) | |
| Mean (SD) | 61.1 (11.7) | 70.9 (11.3) | |
| Median (min, max) | 60.9 (33.9, 89.4) | 71.8 (36.4, 98.4) | |
| Gender | Male | 330 (32%) | 515 (39%) |
| Female | 711 (68%) | 809 (61%) | |
| Body Mass Index | Mean (SD) | 31.7 (7.3) | 29.6 (6.7) |
| Hypertension | No | 280 (27%) | 254 (19%) |
| Yes | 761 (73%) | 1069 (81%) | |
| Taking Hypertension Medication | No | 298 (29%) | 273 (21%) |
| Yes | 730 (71%) | 1043 (79%) | |
| Diabetes | No | 583 (56%) | 797 (60%) |
| Yes | 458 (44%) | 524 (40%) | |
| Taking Diabetes Medication | No | 597 (59%) | 843 (64%) |
| Yes | 423 (41%) | 472 (36%) | |
| Smoking Status | Never Smoker | 437 (47%) | 551 (45%) |
| Former Smoker | 349 (37%) | 527 (43%) | |
| Current Smoker | 147 (16%) | 157 (13%) | |
| History of Alcohol Use | No | 499 (53%) | 812 (66%) |
| Yes | 443 (47%) | 424 (34%) | |
| Past Retinal Surgery | No | 971 (93%) | 1212 (92%) |
| Yes | 70 (7%) | 112 (8%) | |
| Taking Non-Glaucoma Ocular Medications | No | 1011 (97%) | 1305 (99%) |
| Yes | 30 (3%) | 19 (1%) | |
| Any Ocular Comorbidities | No | 174 (18%) | 78 (6%) |
| Yes | 813 (82%) | 1225 (94%) | |
| Age-Related Macular Degeneration | No | 981 (99%) | 1296 (99%) |
| Yes | 6 (1%) | 7 (1%) | |
| Blind (VA 20/200 or worse) | No | 968 (98%) | 1177 (90%) |
| Yes | 19 (2%) | 126 (10%) | |
| Cataract (Nuclear Sclerosis) | No | 388 (39%) | 393 (30%) |
| Yes | 599 (61%) | 910 (70%) | |
| Pseudophakia | No | 863 (83%) | 912 (69%) |
| Yes | 178 (17%) | 412 (31%) | |
| Diabetic Retinopathy | No | 893 (90%) | 1201 (92%) |
| Yes | 94 (10%) | 102 (8%) | |
| Optic Neuropathy | No | 984 (100%) | 1293 (99%) |
| Yes | 3 (0%) | 10 (1%) | |
| Glaucoma Diagnosis | Unilateral | 0 (0%) | 66 (5%) |
| Bilateral | 0 (0%) | 1239 (95%) | |
| No Glaucoma | 1003 (100%) | 0 (0%) | |
| Normal (Low) Tension Glaucoma | No | 987 (100%) | 1263 (97%) |
| Yes | 0 (0%) | 40 (3%) | |
| Mixed Mechanism Glaucoma | No | 987 (100%) | 1270 (97%) |
| Yes | 0 (0%) | 33 (3%) | |
| Past Glaucoma Surgery | No | 1039 (100%) | 857 (65%) |
| Yes | 2 (0%) | 467 (35%) | |
| Taking Glaucoma Medications | No | 1040 (100%) | 438 (33%) |
| Yes | 1 (0%) | 886 (67%) |
FH AND POAG RISK
Self-reported FH was associated with increased risk of POAG (age-adjusted odds ratio and 95% confidence interval 3.4[2.8, 4.1], Table 2). This association was observed in patients with a sibling (3.5[2.7, 4.7]), mother (2.3[1.8, 2.9]), father (3.3[2.3, 4.7]), or child (2.6[1.2, 6.1]) with glaucoma.
Table 2.
Association of Family History of Glaucoma with Primary Open-Angle Glaucoma Risk in African Americans.
| Characteristic | Case vs Control | |||||
|---|---|---|---|---|---|---|
| N (%) n=2365 |
Controls n=1041 (44%) |
Cases n=1324 (56%) |
OR (95% CI) |
Age-adjusted OR (95% CI) |
||
| Any family member | Positive | 1133 (47.9%) | 357 (34.3%) | 776 (58.6%) | 2.71 (2.29, 3.21) | 3.38 (2.80, 4.09) |
| Negative | 1232 (52.1%) | 684 (65.7%) | 548 (41.4%) | reference | reference | |
| First degree relative | Positive | 830 (35.1%) | 214 (20.6%) | 616 (46.5%) | 3.36 (2.80, 4.05) | 3.43 (2.81, 4.19) |
| Negative | 1535 (64.9%) | 827 (79.4%) | 708 (53.5%) | reference | reference | |
| Parent | Positive | 581 (24.6%) | 170 (16.3%) | 411 (31.0%) | 2.31 (1.89, 2.83) | 2.75 (2.21, 3.42) |
| Negative | 1784 (75.4%) | 871 (83.7%) | 913 (69.0%) | reference | reference | |
| Mother | Positive | 429 (18.1%) | 129 (12.4%) | 300 (22.7%) | 2.07 (1.66, 2.60) | 2.30 (1.81, 2.93) |
| Negative | 1936 (81.9%) | 912 (87.6%) | 1024 (77.3%) | reference | reference | |
| Father | Positive | 206 (8.7%) | 53 (5.1%) | 153 (11.6%) | 2.44 (1.77, 3.39) | 3.28 (2.33, 4.68) |
| Negative | 2159 (91.3%) | 988 (94.9%) | 1171 (88.4%) | reference | reference | |
| Siblings | Positive | 399 (16.9%) | 77 (7.4%) | 322 (24.3%) | 4.02 (3.11, 5.27) | 3.52 (2.68, 4.67) |
| Negative | 1966 (83.1%) | 964 (92.6%) | 1002 (75.7%) | reference | reference | |
| Child | Positive | 54 (2.3%) | 8 (0.8%) | 46 (3.5%) | 4.65 (2.31, 10.7) | 2.56 (1.23, 6.06) |
| Negative | 2311 (97.7%) | 1033 (99.2%) | 1278 (96.5%) | reference | reference | |
OR=odds ratio
The relationship of FH with POAG risk did not significantly vary across age groups (2.9 [2.1, 4.0] in participants <60 years; 3.2 [2.3, 4.4] 60-69 years; 4.5 [3.0, 6.6] 70-79 years; 4.0 [2.1, 8.2] 80+ years; Supplementary Table 2). The association between positive FH and POAG risk was very similar between genders, with an age-adjusted odds ratio of 3.7 (2.6, 5.1) for males and 3.7 (2.9, 4.7) for females (Supplementary Table 3).
FH AND BASELINE CHARACTERISTICS, COMORBIDITIES, AND LIFESTYLE CHOICES IN CASES
Table 3 shows the comparison of baseline characteristics, comorbidities, and lifestyle choices between POAG cases with versus without positive FH. Cases with positive FH were approximately three years younger (P<.001) and more likely to be female (66.6% vs. 53.3%, age-adjusted P<0.001) than cases without FH. Cases with positive FH were also more likely to have hypertension (82.3% vs. 78.6%, age-adjusted P=.006) and to take medication for hypertension (80.3% vs. 77.7%, age-adjusted P=.03). No relationship was detected between positive FH and lifestyle related factors such as body mass index, smoking status, and alcohol use.
Table 3.
Association of Family History of Glaucoma with Patient Characteristics among Cases.
| n (%) | p-value | ||||
|---|---|---|---|---|---|
| Characteristic | Level | Cases without FH (N=548) |
Cases with FH (N=776) |
Unadjusted | Age-Adjusted |
| Age | Mean (SE) | 72.5 (0.49) | 69.8 (0.39) | <0.001 | <0.001 |
| Gender | Male | 256 (46.7%) | 259 (33.4%) | <0.001 | <0.001 |
| Female | 292 (53.3%) | 517 (66.6%) | |||
| Body Mass Index | Mean (SE) | 29.2 (0.28) | 29.9 (0.25) | 0.10 | 0.54 |
| Hypertension | No | 117 (21.4%) | 137 (17.7%) | 0.09 | 0.006 |
| Yes | 430 (78.6%) | 639 (82.3%) | |||
| Taking Hypertension Medication | No | 121 (22.3%) | 152 (19.7%) | 0.25 | 0.03 |
| Yes | 422 (77.7%) | 621 (80.3%) | |||
| Diabetes | No | 325 (59.5%) | 472 (60.9%) | 0.61 | 0.72 |
| Yes | 221 (40.5%) | 303 (39.1%) | |||
| Taking Diabetes Medication | No | 338 (62.1%) | 505 (65.5%) | 0.21 | 0.22 |
| Yes | 206 (37.9%) | 266 (34.5%) | |||
| Smoking Status | Never Smoker | 223 (44.3%) | 328 (44.8%) | 0.82 | 0.89 |
| Former Smoker | 219 (43.5%) | 308 (42.1%) | |||
| Current Smoker | 61 (12.1%) | 96 (13.1%) | |||
| History of Alcohol Use | No | 334 (66.3%) | 478 (65.3%) | 0.72 | 0.62 |
| Yes | 170 (33.7%) | 254 (34.7%) | |||
| Past Retinal Surgery | No | 504 (92.0%) | 708 (91.2%) | 0.64 | 0.58 |
| Yes | 44 (8.0%) | 68 (8.8%) | |||
| Taking non-Glaucoma Ocular Medications | No | 542 (98.9%) | 763 (98.3%) | 0.39 | 0.41 |
| Yes | 6 (1.1%) | 13 (1.7%) | |||
| Any Ocular Comorbidities | No | 30 (5.5%) | 48 (6.3%) | 0.55 | 0.52 |
| Yes | 513 (94.5%) | 712 (93.7%) | |||
| Age Related Macular Degeneration | No | 538 (99.1%) | 758 (99.7%) | 0.13 | 0.20 |
| Yes | 5 (0.9%) | 2 (0.3%) | |||
| Blind (VA 20/200 or worse) | No | 488 (89.9%) | 689 (90.7%) | 0.63 | 0.82 |
| Yes | 55 (10.1%) | 71 (9.3%) | |||
| Cataract (Nuclear Sclerosis) | No | 180 (33.1%) | 213 (28.0%) | 0.047 | 0.055 |
| Yes | 363 (66.9%) | 547 (72.0%) | |||
| Pseudophakia | No | 358 (65.3%) | 554 (71.4%) | 0.02 | 0.47 |
| Yes | 190 (34.7%) | 222 (28.6%) | |||
| Diabetic Retinopathy | No | 499 (91.9%) | 702 (92.4%) | 0.75 | 0.89 |
| Yes | 44 (8.1%) | 58 (7.6%) | |||
| Optic Neuropathy | No | 540 (99.4%) | 753 (99.1%) | 0.46 | 0.59 |
| Yes | 3 (0.6%) | 7 (0.9%) | |||
| Glaucoma Diagnosis | Unilateral | 24 (4.4%) | 42 (5.5%) | 0.38 | 0.41 |
| Bilateral | 519 (95.6%) | 720 (94.5%) | |||
| Normal (Low) Tension Glaucoma | No | 524 (96.5%) | 739 (97.2%) | 0.45 | 0.37 |
| Yes | 19 (3.5%) | 21 (2.8%) | |||
| Mixed Mechanism Glaucoma | No | 526 (96.9%) | 744 (97.9%) | 0.25 | 0.27 |
| Yes | 17 (3.1%) | 16 (2.1%) | |||
| Past Glaucoma Surgery | No | 369 (67.3%) | 488 (62.9%) | 0.10 | 0.02 |
| Yes | 179 (32.7%) | 288 (37.1%) | |||
| Taking Glaucoma Medications | No | 190 (34.7%) | 248 (32.0%) | 0.30 | 0.26 |
| Yes | 358 (65.3%) | 528 (68.0%) | |||
FH=family history; SE=standard error
FH AND OCULAR CHARACTERISTICS IN CASES
Ocular characteristics including VA, CDR, maximum IOP, CCT, RNFL, and mean deviation (MD) were compared between POAG cases with versus without positive FH, as shown in Table 4. Cases with positive FH were more likely to have an IOP > 30mmHg (19.7% vs. 17.5%, age-adjusted P=.055) and an overall RNFL thickness > 80 μm (32.2% vs. 23.7%, age-adjusted P=.03). VA, CDR, CCT, and MD did not differ significantly between POAG cases with and without FH of glaucoma.
Table 4.
Association of Family History of Glaucoma with Ocular Characteristics Among Cases.
| n (%) | p-value | ||||
|---|---|---|---|---|---|
| Ocular Characteristics | Level | Cases without FH (N=1060 eyes) |
Cases with FH (N=1480 eyes) |
Unadjusted | Age-Adjusted |
| logMAR Visual Acuity | 20/20 or better | 218 (27.2%) | 424 (36.5%) | 0.002 | 0.12 |
| Worse than 20/20, 20/40 or better | 348 (43.4%) | 466 (40.1%) | |||
| Worse than 20/40, better than 20/200 | 154 (19.2%) | 166 (14.3%) | |||
| 20/200 or worse | 82 (10.2%) | 106 (9.1%) | |||
| Mean (SE) | 0.36 (0.020) | 0.31 (0.017) | 0.13 | 0.50 | |
| Cup-to-Disc ratio | <0.5 | 106 (11.6%) | 113 (8.6%) | 0.18 | 0.19 |
| 0.5 to 0.8 | 557 (60.9%) | 819 (62.1%) | |||
| >0.8 | 252 (27.5%) | 387 (29.3%) | |||
| Mean (SE) | 0.71 (0.0060) | 0.72 (0.0048) | 0.44 | 0.39 | |
| Max Intraocular Pressure (mmHg) | <21 | 404 (38.2%) | 476 (32.5%) | 0.07 | 0.055 |
| 21 to 30 | 469 (44.3%) | 701 (47.8%) | |||
| >30 | 185 (17.5%) | 289 (19.7%) | |||
| Mean (SE) | 24.6 (0.26) | 25.2 (0.22) | 0.17 | 0.20 | |
| Central Corneal Thickness (μm) | <500 | 182 (19.3%) | 278 (21.2%) | 0.40 | 0.19 |
| 500 to 540 | 391 (41.5%) | 567 (43.2%) | |||
| >540 | 370 (39.2%) | 467 (35.6%) | |||
| Mean (SE) | 531 (1.29) | 529 (1.10) | 0.49 | 0.29 | |
| Retinal Nerve Fiber Layer Thickness (μm) | <60 | 130 (21.2%) | 180 (19.5%) | 0.007 | 0.03 |
| 60 to 80 | 338 (55.1%) | 446 (48.3%) | |||
| >80 | 145 (23.7%) | 297 (32.2%) | |||
| Mean (SE) | 71.0 (0.54) | 73.4 (0.50) | 0.01 | 0.08 | |
| Mean Deviation (dB) | <−10 | 210 (33.3%) | 235 (27.4%) | 0.17 | 0.41 |
| −10 to −3 | 186 (29.5%) | 269 (31.4%) | |||
| >−3 to <0 | 174 (27.6%) | 248 (28.9%) | |||
| >=0 | 60 (9.5%) | 106 (12.4%) | |||
| Mean (SE) | 71.0 (0.54) | 73.4 (0.50) | 0.22 | 0.39 | |
DISCUSSION
FH and POAG Risk
More than 35% of POAAGG subjects reported a positive FH of glaucoma in a first-degree relative. In contrast, the Baltimore Eye Survey and Barbados Eye Study reported that only 16.1%17 and 17%27 of cases had positive FH of glaucoma in a first-degree relative, respectively. The Ocular Hypertension Treatment Study, on the other hand, showed that 42% of participants reported a positive FH of glaucoma in any relative.28 We believe that our higher rate of reported FH may be due to the unusually high prevalence of POAG in African Americans, especially among older individuals.
Positive FH in a first-degree relative was associated with a 3.4 odds ratio of having POAG. The Baltimore Eye Survey and the Barbados Eye Study reported slightly lower odds ratios (3.1[1.9, 5.2]; 2.4[1.4, 4.2]),17,19 while other studies, such as a case-control study in the Congo, found that positive FH conferred up to an 18-fold higher risk of POAG.20 These studies had much smaller cohorts (POAAGG, 2365; Congo, 144) with potentially different ancestry, and used slightly different definitions of OAG, possibly accounting for these differences in risk. The POAAGG definition of glaucoma was particularly stringent, requiring diagnosis by a glaucoma specialist of a characteristic optic nerve appearance and a corresponding visual field defect.
Age-adjusted associations of POAG with FH were highest in siblings, which is consistent with the findings of the Baltimore Eye Survey and Barbados Eye Study.17,19 Interestingly, paternal FH had a higher association with POAG than maternal FH (3.3[2.3, 4.7] vs. 2.3[1.8, 2.9]), conflicting with many reports in literature.21,22,29,30 Evaluating FH can introduce many biases, specifically recall bias as subjects have a tendency to know maternal lineage better than paternal lineage.31 We did not observe this commonly cited recall bias.
FH AND CHARACTERISTICS IN CASES
Cases with positive FH were younger than those without FH, suggesting that FH may contribute to earlier onset of POAG. It is interesting that females were more likely to report positive FH of POAG, while males were more likely to develop the disease.32 African American women play an important role as conduits and recorders of family health information, perhaps leading to better knowledge and higher reporting rates of FH information.33
While those with positive FH were more likely to have hypertension or take medications for hypertension, the majority of previous studies found no relationship between hypertension and POAG.27,31,34 Maximum IOP was higher in cases with positive FH, as were rates of past glaucoma surgery. These findings may well be correlated. Patients presenting with higher maximum IOP may be considered at an earlier stage for surgical as opposed to pharmacologic intervention. The younger age, higher maximum IOP, and greater rates of past glaucoma surgery all point towards a more severe form of POAG in cases with positive FH.
RNFL thickness measured by optical coherence tomography (OCT) is useful in detecting early RNFL damage and monitoring glaucomatous changes over time.35 This study found that cases with positive FH were more likely to have a RNFL value >80 μm. This is a surprising result, as other data (younger age, higher maximum IOP, more glaucoma surgeries) suggests more severe disease in this group, which is typically associated with thinner RNFL.26 It is possible that patients with a known positive FH of POAG are more likely to actively seek preventative care, which could detect disease prior to significant RNFL loss. Additionally, thicker RNFL may be a characteristic of a glaucoma sub-type existing within our study population. Groups have previously found that RNFL thickness is determined by genetic effects,36 so it is possible that some cases with positive FH demonstrate the phenotypes associated with different genetic variants underlying their disease. Future research will explore this possibility, as well as the other nuclear and mitochondrial variants underlying POAG in African Americans. Genome-wide association studies and whole exome sequencing are currently in progress.
STUDY LIMITATIONS
One potential flaw in this study’s design is the reliance on self-reporting in data collection, which can be subject to recall bias. The Baltimore Eye Survey showed previously diagnosed individuals reported FH of glaucoma significantly more often than newly diagnosed individuals.17 Because FH was captured at time of enrollment, subjects with newly diagnosed POAG may have incomplete FH information. Nevertheless, other large epidemiological studies have shown that self-reporting is accurate among various ethnic groups32 and correlates well with medical records,37 for a number of co-morbidities32 and health care utilization rates.38
Additionally, the clinic-based method of enrollment of the POAAGG study could introduce some bias. It is possible that positive FH served as an impetus for some glaucoma patients to make an eye appointment (more so than controls), contributing to this group’s higher rates of reported FH. The POAAGG study has obtained additional grants for a van and a complete suite of glaucoma equipment, which provides outreach to senior centers in Philadelphia.
Furthermore, it is possible that the rate of reported FH is inflated in this study due to subjects incorrectly identifying family members as having glaucoma. Some family members may actually be glaucoma suspects or have ocular hypertension without damage. In the literature, one study showed that FH reporting had 77% sensitivity in identifying relatives with coronary heart disease,39 while another study showed complete agreement between reported information and diabetes status among relatives.40 Diseases involving some stigma (such as alcoholism or schizophrenia) may be reported less reliably.41 Thus, we acknowledge that the rates of FH may be elevated due to this bias, but believe these studies show that the results can still be reported.
Lastly, the transition in data collection from CRFs to REDCap over the study period may have impacted results, as data collected before November 2012 was obtained from a less detailed survey. We supplemented this data by consulting electronic medical records, recontacting patients, and verifying data accuracy through our random sampling of 200 patients.
Supplementary Material
Acknowledgments
FUNDING/SUPPORT
This work was supported by the National Eye Institute, Bethesda, Maryland (grant #1RO1EY023557-01) and the Department of Ophthalmology at the Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA. Funds also come from the F.M. Kirby Foundation, Research to Prevent Blindness, The UPenn Hospital Board of Women Visitors, The Paul and Evanina Bell Mackall Foundation Trust, and the National Eye Institute, National Institutes of Health, Department of Health and Human Services, under eyeGENETM and contract Nos. HHSN260220700001C and HHSN263201200001C. The sponsor or funding organization had no role in the design or conduct of this research.
Footnotes
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FINANCIAL DISCLOSURES
N/A
AUTHOR CONTRIBUTIONS
Design and conduct of the study (JMO, GSY); collection, management, analysis, and interpretation of the data (all authors); drafting of manuscript (JMO, RS, KG, MH); and preparation, review, or approval of the manuscript (all authors).
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