Glaucoma is a heterogeneous and multifactorial neurodegenerative disease, which is predicted to affect 112 million people worldwide in 2040 [
Platelet function and platelet-endothelial interactions are involved in the ocular microcirculation, with implications based on clinical and experimental evidence. Watanabe et al. [
To better understand platelet activation in POAG, we performed a retrospective study to measure platelet parameters in patients with POAG and to explore a possible association between platelet parameters and POAG severity.
This study was approved by the Ethics Review Committee of Eye and Ear, Nose, Throat Hospital (EENT), Fudan University. The design and implement of this study adhered to the tenets of the Declaration of Helsinki. Written informed consent was obtained from all the patients.
Patients were consecutively recruited in the Eye and ENT Hospital, Fudan University, from January 2016 to October 2018. A total of 520 participants were recruited, of whom 118 (secondary glaucoma = 22, congenital glaucoma = 8, other concomitant eye diseases = 19, normal tension glaucoma = 11, receive antiplatelets/anticoagulants medications mentioned in exclusion criteria = 12, renal diseases = 8, hematological diseases = 1, thyroid dysfunction = 9, cardiovascular diseases = 10, hepatic diseases = 8, acute infectious diseases = 3, autoimmune diseases = 6, and cancer = 1) were later excluded, leaving a final sample of 402 patients.
The definition of POAG was based on (1) glaucomatous optic neuropathy such as a vertical cup disk ratio (VCDR) > 0.7 or an inter-eye asymmetry of >0.2, with notching, rim thinning, or retina nerve fiber layer (RNFL) defect; (2) visual field defect that corresponds to the structural change: presence of at least three contiguous nonedged test points within the same hemifield on the corrected probability plot at
Excluded from this study were patients with congenital, secondary glaucoma or history of intraocular surgery. Patients with concomitant ocular diseases, which could potentially impair visual fields such as optic disk anomalies, optic nerve diseases, retinal diseases, pathologic myopia, and intracranial lesions, were excluded. A review of systemic diseases was conducted, and patients who met the following criteria were also excluded: (1) <18 years old or pregnant woman; (2) hematological diseases such as aplastic anaemia, purpura haemorrhagica, and primary thrombocytosis; (3) abnormal coagulation function; (4) severe cardiovascular, hepatic, or renal diseases; (5) recent surgery or trauma; (6) cancer; (7) acute infectious diseases or autoimmune diseases; (8) thyroid dysfunction; (9) use of antiplatelets/anticoagulants medications during the previous 6 months such as aspirin, clopidogrel, warfarin, and cilostazol [
Healthy controls were consecutively recruited from individuals who participated in yearly health screenings during the study period. A total of 500 individuals were recruited, of whom 92 (receive antiplatelets/anticoagulants medications = 21, eye diseases = 15, IOP ≥ 21 mmHg = 4, VCDR > 0.5 = 7, thyroid dysfunction = 10, cardiovascular diseases = 15, hepatic diseases = 6, renal diseases = 3, acute infectious diseases = 2, autoimmune diseases = 4, recent surgery = 2, and cancer = 3) were later excluded from the study according to the inclusion criteria, leaving a final sample of 408 control subjects.
Inclusion criteria: IOP < 21 mmHg; age 18 years and older; normal-appearing optic discs; anterior chamber angle open; VCDR ≤ 0.5. Exclusion criteria: family history or personal history of glaucoma; complaints of eye discomfort; prior ocular trauma or surgery; severe systemic diseases.
All the enrolled POAG subjects in the study were inpatients, and blood samples were drawn for laboratory measurements at the same day that standardized ophthalmic examination and comprehensive physical examination were performed. Each subject underwent a thorough ophthalmological examination conducted by a glaucoma specialist. Gonioscopy was performed for all the recruited patients, to determine anterior chamber angle. Visual fields mean deviation (MD) and visual fields mean sensitivity (MS) were measured with the Octopus automated perimeter (HAAG, STREIT, Switzerland). The intraocular pressure (IOP) was measured 3 times with a Goldmann applanation tonometer, and the average value was determined. Fundus photography was performed using a digital retinal camera (TRC- NW200, Topcon). Each control individual underwent preliminary ophthalmic examinations, which included refractive status, gonioscopy, slit-lamp biomicroscopic examination, and IOP, as carried out by glaucoma specialists. Clinical and demographic information was obtained from the medical data platform of the hospital. The subjects’ drinking (>3 times per week and >6 mo (current or former)) and smoking (>1 cigarette per day and >6 mo (current or former)) history (self-reported) were also collected.
Laboratory measurements were performed in the Department of Clinical Laboratory Science, Eye & ENT Hospital. Blood samples for platelet parameters, including platelet count (PLT), platelet distribution width (PDW), plateletcrit (PCT), mean platelet volume (MPV), and platelet large cell ratio (P-LCR), were taken in laboratory tubes with ethylenediaminetetraacetic acid (EDTA) and analyzed using an automated hematology analyzer (Sysmex XN 1000, Japan) within 30 minutes following standard venipuncture of the veins in the antecubital fossae (anterior elbow veins). The reference range of PLT, MPV, PDW, PCT, and P-LCR was (100–400)
POAG has a male predominance [
The data were analyzed by SPSS23.0 (IBM SPSS Statistics) and Microsoft Excel 2016. The results are presented as mean ± standard deviation (SD). The independent Student’s
A total of 402 POAG patients (male = 268; female = 134) and 408 control subjects (male = 258; female = 150) were enrolled. Their mean ages were 51.19 ± 15.69 years and 51.50 ± 8.90 years in POAG and control groups, respectively. If both eyes of the same individual were affected by POAG, only one eye was randomly selected. The POAG group and control group were closely matched in terms of mean age
Demographics and platelet parameters of subjects with POAG.
POAG ( |
Control ( |
|
| |
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Age (y) | 51.19 ± 15.69 | 51.50 ± 8.90 | −0.341 | 0.733 |
Female/male | 134/268 | 150/258 | 1.047 | 0.338 |
BMI | 24.31 ± 3.47 | 24.13 ± 3.38 | 0.426 | 0.670 |
Hypertension (yes/no) | 75/327 | 58/350 | 2.910 | 0.107 |
Diabetes (yes/no) | 31/371 | 36/372 | 0.330 | 0.611 |
Smoking (yes/no) | 62/340 | 56/352 | 0.469 | 0.550 |
Drinking (yes/no) | 73/329 | 68/340 | 0.314 | 0.580 |
PLT (109/L) | 207.08 ± 54.70 | 220.46 ± 55.85 | −3.392 |
|
PDW (fL) | 13.76 ± 3.16 | 11.82 ± 2.44 | 9.571 |
|
PCT (%) | 0.21 ± 0.05 | 0.22 ± 0.05 | −2.009 |
|
MPV (fL) | 10.46 ± 1.32 | 10.13 ± 1.10 | 3.810 |
|
P-LCR (%) | 27.57 ± 9.14 | 26.13 ± 8.50 | 1.915 | 0.056 |
Independent-samples
Table
According to their age and gender, POAG and control subjects were divided into male (a <50 subgroup, and a ≥50 subgroup) and female subgroups (a <50 subgroup and a ≥50 subgroup). In both the gender and age subgroups, the PDW and MPV levels were significantly higher (all
Comparison of platelet parameters in subjects with POAG, stratified according to gender and age.
Subgroups | POAG ( |
Control ( |
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Male | ||||
<50 ( |
210.18 ± 52.23 | 227.53 ± 53.51 | −2.614 |
|
≥50 ( |
190.62 ± 47.83 | 203.81 ± 51.53 | −2.107 |
|
Female | ||||
<50 ( |
227.19 ± 58.51 | 234.32 ± 53.53 | −0.671 | 0.504 |
≥50 ( |
206.73 ± 48.66 | 222.64 ± 48.95 | −2.048 |
|
|
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Male | ||||
<50 | 13.95 ± 2.99 | 11.70 ± 2.30 | 6.712 |
|
≥50 | 13.63 ± 3.28 | 11.76 ± 2.42 | 5.190 |
|
Female | ||||
<50 | 13.84 ± 3.52 | 12.40 ± 2.80 | 2.349 |
|
≥50 | 13.63 ± 3.05 | 11.63 ± 2.35 | 4.639 |
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Male | ||||
<50 | 0.22 ± 0.04 | 0.23 ± 0.05 | −1.373 | 0.171 |
≥50 | 0.20 ± 0.05 | 0.20 ± 0.05 | −0.601 | 0.548 |
Female | ||||
<50 | 0.24 ± 0.06 | 0.24 ± 0.06 | −0.433 | 0.666 |
≥50 | 0.21 ± 0.05 | 0.22 ± 0.04 | 2.293 | 0.296 |
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Male | ||||
<50 | 10.54 ± 1.38 | 10.09 ± 1.01 | 2.921 |
|
≥50 | 10.40 ± 1.34 | 10.07 ± 1.05 | 2.207 |
|
Female | ||||
<50 | 10.68 ± 1.20 | 10.23 ± 1.00 | 2.151 |
|
≥50 | 10.47 ± 1.14 | 10.06 ± 1.13 | 2.293 |
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Male | ||||
<50 | 27.67 ± 9.22 | 25.66 ± 8.10 | 1.530 | 0.128 |
≥50 | 27.65 ± 8.52 | 25.70 ± 8.18 | 1.585 | 0.114 |
Female | ||||
<50 | 26.42 ± 9.67 | 28.25 ± 9.50 | −0.848 | 0.399 |
≥50 | 27.99 ± 9.88 | 25.81 ± 8.64 | 1.280 | 0.203 |
Independent-samples
On the basis of the MD, the POAG subjects were categorized into 3 subgroups of different disease-severity levels, whereby 70 subjects were classified as mild, 94 as moderate, and 238 as severe. A comparison of platelet parameters and ocular parameters in the POAG subjects is shown in Table
Comparison of demographics, platelet parameters, and ocular parameters in subjects with POAG, stratified according to severity.
Factors | Mild POAG ( |
Moderate POAG ( |
Severe POAG ( |
|
---|---|---|---|---|
Age (y) | 50.53 ± 16.00 | 51.83 ± 15.60 | 50.74 ± 15.66 | 0.882 |
Female/male | 24/46 | 37/57 | 73/165 | 0.313 |
BMI | 23.21 ± 2.79 | 23.58 ± 2.91 | 24.92 ± 3.68 |
|
IOP (mm·Hg) | 19.30 ± 6.60 | 20.43 ± 8.53 | 25.74 ± 11.21 |
|
VCDR | 0.60 ± 0.20 | 0.71 ± 0.19 | 0.87 ± 0.13 |
|
MD (dB) | 4.13 ± 1.28 | 9.34 ± 1.61 | 22.45 ± 5.53 |
|
MS (dB) | 23.39 ± 1.45 | 18.25 ± 1.87 | 6.24 ± 4.95 |
|
PLT (109/L) | 217.43 ± 48.11 | 218.16 ± 54.98 | 200.77 ± 52.18 |
|
PDW (fL) | 11.82 ± 2.44 | 12.50 ± 3.14 | 14.49 ± 2.99 |
|
PCT (%) | 0.21 ± 0.04 | 0.22 ± 0.05 | 0.21 ± 0.05 | 0.744 |
MPV (fL) | 9.92 ± 0.76 | 10.02 ± 1.08 | 10.74 ± 1.39 |
|
P-LCR (%) | 24.35 ± 5.90 | 24.58 ± 7.41 | 30.12 ± 9.71 |
|
Comparison of (a) platelet (PLT), (b) platelet distribution width (PDW), (c) mean platelet volume (MPV), and (d) platelet large cell ratio (P-LCR) levels in patients with mild, moderate, and severe primary open-angle glaucoma (POAG) and the control group. Each data point represents one subject. The medium bar represents the mean; the top and bottom bars represent the standard deviation.
Spearman correlation analyses were performed to identify the association between platelet parameters and ocular parameters in patients with POAG (Table
Correlation between platelet parameters and glaucoma severity in POAG.
Factors | IOP | VCDR | MD | MS |
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PLT |
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PDW |
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MPV |
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P-LCR |
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PCT |
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POAG: primary open-angle glaucoma; PLT: platelet count; PDW: platelet distribution width; PCT: plateletcrit; MPV: mean platelet volume; P-LCR: platelet large cell ratio; IOP, intraocular pressure; VCDR, vertical cup-disc ratio; MD, visual field mean deviation; MS, visual fields mean sensitivity. One-sample Kolmogorov–Smirnov test
Scatterplot of patient individual measurements for visual field median deviation (MD) and visual field mean sensitivity (MS) versus platelet (PLT), platelet distribution width (PDW) and mean platelet volume (MPV) levels; each data point represents one patient. Linear regression is displayed.
Multiple linear regressions for associations between platelet parameters and ocular parameters in patients with POAG.
VCDR |
MD |
MS | |
---|---|---|---|
PLT | −0.166 (0.097, −98.50 to 8.39) | −0.182 (0.073, −1.982 to 0.092) | 0.173 (0.161, −0.377 to 2.228) |
PDW | 0.145 (0.167, −1.136 to 6.450) | 0.430 (<0.001, 0.083 to 0.218) | −0.317 (0.009, −0.191 to −0.028) |
MPV | 0.209 (0.050, 0.003 to 3.023) | 0.363 (0.001, 0.022 to 0.078) | −0.359 (0.003, −0.081 to −0.017) |
Adjusting for age, gender, body mass index, hypertension, diabetes, drinking, and smoking. 95% CI: 95% confidence interval; POAG: primary open-angle glaucoma; PLT: platelet count; PDW: platelet distribution width; PCT: plateletcrit; MPV: mean platelet volume; P-LCR: platelet large cell ratio; VCDR: vertical cup-disc ratio; MD: visual fields mean deviation; MS: visual fields mean sensitivity.
Logistic regression analyses were performed to identify the association between platelet parameters and severity of POAG (Table
Logistic regression analysis of the association between platelet parameters and severity of POAG.
OR |
|
95% CI | |
---|---|---|---|
Age | 1.012 | 0.585 | 0.971–1.054 |
Gender | 0.820 | 0.709 | 0.289–2.326 |
BMI | 1.195 |
|
1.014–1.409 |
Hypertension | 2.403 | 0.309 | 0.444–13.018 |
Diabetes | 2.560 | 0.287 | 0.454–14.449 |
Smoking | 1.105 | 0.881 | 0.299–4.079 |
Drinking | 1.380 | 0.588 | 0.430–4.435 |
PDW | 1.297 |
|
1.011–1.663 |
MPV | 1.055 | 0.862 | 0.574–1.940 |
PLT | 0.995 | 0.431 | 0.984–1.007 |
Logistic regression analyses were performed to identify the association between platelet parameters and severity of primary open-angle glaucoma (POAG) (mild and moderate POAG group = 1; severe POAG group = 2) (male = 1, female = 2; no hypertension = 1, hypertension = 2; no diabetes = 1, diabetes = 2; no drinking = 1, drinking = 2; no smoking = 1, smoking = 2). 95% CI: 95% confidence interval; POAG: primary open-angle glaucoma; BMI: body mass index; PLT: platelet count; PDW: platelet distribution width; MPV: mean platelet volume.
To the best of our knowledge, this is the first study to evaluate the potential relationship between platelet parameters and POAG. Our results indicated that POAG patients had significantly lower platelet counts and significantly higher PDW and MPV levels than control subjects. The PDW and MPV levels were highest in the severe POAG group, followed by the moderate POAG group and then the mild POAG group. Logistic regression analyses revealed that PDW was associated with the severity of POAG. Our results suggest altered platelet activation in POAG patients.
Platelets play a vital role in the coagulation cascade and in vascular pathophysiology [
Ocular blood flow alterations in glaucoma patients seem, at least partly, to be associated with systemic vascular dysregulation. Platelet parameters, especially platelet activation parameters, have been reported to be related to several ocular diseases and cardiovascular event. T. Yilmaz and A. Yilmaz [
Reduced ocular blood flow is related to the progression of visual field loss in glaucoma [
Logistic regression analyses revealed that PDW was independently associated with severity of POAG. PDW is a more direct marker to represent platelet reactivity than MPV since it was not elevated during single platelet distention caused by platelet swelling [
The platelet parameter values of most patients with POAG were still within the reference range, thus we consider platelet function may not be the primary cause of POAG but may be a secondary factor that could increase the risk of POAG and be involved in disease development. However, our results might provide a vital novel field for researchers to study the pathophysiological mechanism of POAG. Considering that vascular dysregulation is commonly recognized to be involved in glaucoma, it is worth exploring the possible mechanism of vascular dysregulation in glaucoma. Moreover, platelet activation, either secondary to vascular dysregulation or resulting in vascular dysregulation, can be well monitored in a clinical laboratory.
We acknowledge that our present study has some limitations. Firstly, our study was a single-center, retrospective analysis. The results might be affected by confounding factors, despite that multiple linear regression analysis was performed to adjust for age, gender, BMI, hypertension, diabetes, smoking, and drinking status. Therefore, large-scale, multi-center prospective studies are required to better investigate the relationship between platelet parameters and POAG. Secondly, due to the inherent deficiencies of retrospective methods, we cannot judge the causality. The mechanism of platelet activation in the pathogenesis of glaucomatous optic neuropathy is worth further exploration in our follow-up study. Moreover, visual field testing was not performed in healthy controls since it is not a routine eye examination in our hospital, although each control individual underwent preliminary ophthalmic examinations.
To the best of our knowledge, this is the first study to assess a potential relationship between platelet parameters and POAG. We found that POAG patients have higher PDW, which has a significant positive correlation with POAG severity. Our results provide further evidence of the vascular dysregulation in POAG, raising the possibility of modulating platelet activation as a potential therapeutic measure.
The data used to support the findings of this study are available from the corresponding author upon request.
The submission is not under review at any other publication, in whole or in part, and all the authors listed have approved the enclosed manuscript. All the authors declare no financial conflicts of interest and have fulfilled the criteria of authorship for the manuscript.
This research project was supported by grants from the subject of major projects of the National Natural Science Foundation of China (81790641) and Shanghai Municipal Commission of Health and Family Planning (201840050).