December 2007
Volume 48, Issue 12
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Clinical and Epidemiologic Research  |   December 2007
Circulating Hematopoietic Stem Cells in Patients with Neovascular Age-Related Macular Degeneration
Author Affiliations
  • Yuko Yodoi
    From the Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Manabu Sasahara
    From the Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Takanori Kameda
    From the Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Nagahisa Yoshimura
    From the Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Atsushi Otani
    From the Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Investigative Ophthalmology & Visual Science December 2007, Vol.48, 5464-5472. doi:10.1167/iovs.07-0093
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      Yuko Yodoi, Manabu Sasahara, Takanori Kameda, Nagahisa Yoshimura, Atsushi Otani; Circulating Hematopoietic Stem Cells in Patients with Neovascular Age-Related Macular Degeneration. Invest. Ophthalmol. Vis. Sci. 2007;48(12):5464-5472. doi: 10.1167/iovs.07-0093.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

purpose. Circulating hematopoietic stem cells (HSCs) appear to have roles in the formation of choroidal neovascularization (CNV) in age-related macular degeneration (AMD). This study was conducted to investigate whether the number or function of HSCs plays a role in neovascular AMD.

methods. Eighty-one patients with neovascular AMD who underwent comprehensive fundus examinations every 3 months were included. The number of CD34+ HSCs isolated from peripheral blood was counted by flow cytometry. Serum cytokine levels were assessed by enzyme-linked immunosorbent assay. To examine the function of circulating HSCs, mononuclear cells were cultured and then colony forming unit (CFU-EC) and migration were measured.

results. The number of circulating CD34+ HSCs was significantly increased in the patients with active CNV without major systemic diseases (stable: 3.8 ± 0.3 cells/μL, active: 5.5 ± 0.7 cells/μL, stable versus active: P < 0.05). The number of HSCs correlated positively with the erythropoietin serum level (r = 0.47, P = 0.002). Although there was no significant difference in the CFU-EC between the patients with CNV and the control subjects, a significant decrease of CFU-EC was observed in the patients with bilateral or larger CNV.

conclusions. The findings suggest that CD34+ HSCs may be recruited from bone marrow through a signal from active CNV. Furthermore, HSCs may play a role in the severity of CNV.

Age-related macular degeneration (AMD) is the leading cause of irreversible blindness among the elderly on more than three continents, and its incidence is on the rise. The development of choroidal neovascularization (CNV) is the principal cause of severe vision loss (neovascular AMD). Current therapeutic strategies, including photodynamic therapy and antiangiogenic drugs, focus on reversing neovascularization. 1 In addition to local factors that influence neovascular diseases, recent research strongly suggest systemic factors, including bone marrow–derived stem/progenitor cells, which have an important role in disease severity and prognosis. 
Circulating hematopoietic stem cells (HSCs) derived from bone marrow 2 have been shown to participate in normal and pathologic postnatal angiogenesis. 3 Incorporation of HSCs into retinal 4 and choroidal neovasculature 5 6 has also been reported in an experimental CNV model. However, the role of HSCs in the formation of retinal or choroidal neovasculature remains unclear. 
In addition to the function of HSCs that promote angiogenesis, they also differentiate into a variety of nonendothelial cell types, including hepatocytes, 7 cardiomyocytes, 8 retinal pigment epithelial (RPE) cells, 9 microglia, 10 and even neurons. 11 It has also been suggested that circulating HSCs play important roles in repairing injured tissues 12 13 and disease progression. 14 Because of the variety of functions of HSCs, their precise role in each disease condition may vary and should be carefully examined. 
To investigate whether circulating HSCs act to promote or protect the pathologic state of CNV formation, we examined circulating HSCs from patients with AMD involving CNV, and correlated this with clinical AMD characteristics. We found that the number of CD34+ circulating HSCs increased in patients who had active CNV, but the increase was not related to disease severity. In contrast, the function of circulating HSCs (CFU-EC) was significantly lower AMD with severe CNV than in mild CNV. To our knowledge, this is the first study of circulating HSCs in humans with AMD. 
Materials and Methods
Study Population
The study protocol was approved by the Ethics Committee of Kyoto University Hospital, and all the enrolled subjects gave written informed consent, according to the Declaration of Helsinki. Patients who were diagnosed with neovascular AMD at the Center for Macular Diseases in Kyoto University Hospital from April 2005 to November 2005 were included in the study. All 81 patients underwent comprehensive fundus examinations, including best corrected visual acuity, binocular ophthalmoscopy, slit-lamp biomicroscopy with a contact lens, fundus photograph, fluorescein angiography (FA), indocyanine green angiography (ICGA), and optical coherence tomography. FA and ICGA were simultaneously performed using confocal laser scanning system (HRA2, Heidelberg Engineering, Dossenheim, Germany). Since treatments including photodynamic therapy may affect the results, patients who had received any treatment within 6 months were excluded from this study. Age matched control subjects (n = 21) and young healthy volunteers (n = 10) also provided written informed consent. 
Patient Characteristics and Clinical Evaluation of CNV
We investigated clinical parameters of patients with AMD, including sex, age, best corrected visual acuity, angiographic subtype of CNV, CNV size, laterality of CNV, CNV activity, previous ocular treatments, history of systemic diseases, medication history, and history of smoking. Visual acuity was measured by logarithm of minimum angle of resolution (logMAR). Each patient was classified by three independent investigators (MS, YY, and OA) as having one of three angiographic subtypes of CNV: predominantly classic CNV, minimally classic CNV, and occult CNV. CNV lesion size was based on a fluorescein angiogram, and maximum lesion diameter (greatest linear dimension) was automatically calculated by using software with a confocal laser scanning angiographic system (HRA2 Eye explorer; Heidelberg Engineering). CNV activity was defined as the period of most recent CNV progression. The definition of CNV progression was based on previous clinical trials 15 as follows: (1) a newly occurring hemorrhage associated with CNV, (2) growth of a lesion (at least 10% increase in the greatest linear dimension of the lesion), or (3) a deterioration of the best corrected visual acuity (at least 1 line). The activity of CNV was also evaluated by three independent investigators (MS, YY, and OA). We defined those having active AMD as patients who showed CNV progression over the past 3 months (n = 39) and those with stable AMD as patients without progression of CNV in the past 6 months (n = 42). Age-matched healthy subjects were included as control subjects (n = 21). We used the size and laterality of CNV to judge the severity of CNV lesions in patients with AMD due to data reliability. Present anticoagulant medication and statin medication were investigated. History of smoking was defined according to the Brinkman index (the sum of the number of cigarettes smoked per day multiplied by years of smoking) ≥400. 
Counting the Number of Circulating Hematopoietic Stem Cells
The number of circulating CD34+ HSCs were counted by using flow cytometric analysis. Circulating CD34+ mononuclear cells in the peripheral blood were stained with a reagent kit (ProCount; BD Biosciences, Bedford, MA) and measured with a flow cytometer (FACSCalibur; BD Biosciences). The known amount of stained and lysed, but not washed, blood added to a known amount of microbeads allows, in combination with the observed ratio between the number of flow cytometrically counted beads and CD34+ cells, an absolute CD34+ cell count (Fig. 1) . 16 17 The data were analyzed on computer (Cell Quest software; BD Biosciences). In each blood sample, more than 60,000 cells were counted. An isotype-negative control optimized the settings of the fluorescence detectors for each subject. 
Cytokine Measurements in the Serum of Patients with Neovascular AMD
Serum levels of vascular endothelial growth factor (VEGF), erythropoietin (Epo), angiopoietin (Ang)-1, and stromal cell-derived factor (SDF)-1α were measured using an enzyme-linked immunosorbent assay (ELISA; R&D Systems, Minneapolis, MN). All procedures were performed according to the manufacturer. 
Culture of Hematopoietic Stem Cells and CFU Assay
Culture of the HSCs and the measurement of CFUs were performed as previously described. 18 Mononuclear cells from peripheral blood were collected by light-density gradient centrifugation (Ficoll-Paque Plus; GE Healthcare, Tokyo, Japan), and 1 × 107 of the mononuclear cells were seeded on six-well human fibronectin-coated plates (BD Biosciences) in 2.5 mL of an endothelial basal medium (EBM; Endocult; StemCell Technologies, UK) with 20% fetal bovine serum (FBS). After 48 hours, 1 × 106 nonadherent cells were transferred into new 24-well fibronectin-coated plates in 1 mL of EBM to avoid contamination with mature endothelial cells and nonprogenitor cells. The cells were incubated for another 3 days. After 5 days, the endothelial colonies from three wells were counted by two independent investigators. Immunocytochemistry was performed after fixation with 4% paraformaldehyde, and then the expression of endothelial marker proteins, kinase insert domain receptor (R&D Systems), platelet endothelial cell adhesion molecule-1 (R&D Systems), and vascular endothelial-cadherin (Chemicon, Temecula, CA) were confirmed. 
Migration Assay
After 5 days of in vitro culture, cells were placed in the upper chamber (2.5 × 104) of a modified Boyden chamber with a fluorescence block system 19 (BD BiocoatTM Angiogenesis System: Endothelial Cell Migration, BD Biosciences); performed in duplicate for each patient’s sample. The chamber was placed in a 96-well culture dish containing EBM (Endocul; StemCell Technologies, UK) and 10% FBS. After 22 hours of incubation at 37°C, the lower side of the filter was washed and the migrated cells were stained with a fluorogenic esterase substrate (Calcein AM; Invitrogen-Molecular Probes, Eugene, OR). Migration activity was measured by using a fluorescent plate reader with a bottom-reading system (PerkinElmer, Japan, Osaka, Japan). The data are presented as the percentage of relative fluorescence units with chemoattractants to those without chemoattractant (EBM only). 
Statistical Analysis
All results for continuous variables are expressed as the mean ± SE. Abnormally distributed continuous variables between two groups were compared by Mann-Whitney U test. Comparisons for categorical variables were compared by χ2 test or the Fisher exact probability test for small samples. Multivariate linear regression analysis and nonparametric bivariate correlations (Spearman’s correlation coefficient) were performed to correlate the number of HSCs with risk factors or clinical conditions. Bivariate correlations (age, number of HSCs, serum cytokine levels, CFU-ECs, and migration) were performed by determining the Spearman correlation coefficient. All analyses were performed with a commercial program (SPSS ver. 13.0; SPSS, Chicago, IL). Differences were considered statistically significant at P < 0.05. 
Results
Increased Number of Circulating CD34+ HSCs in Active Neovascular AMD
It is known that CD34+ HSCs are mobilized from bone marrow into the peripheral circulation and participate in the pathogenesis of vascular diseases. To clarify whether HSCs were mobilized in neovascular AMD, we collected and analyzed the peripheral blood of patients with neovascular AMD analyzed (Fig. 2) . Table 1shows clinical characteristics of the patients and the control subjects. The mean number of CD34+ HSCs was higher in all the patients with AMD examined than in the control subjects (4.6 ± 0.3 cells/μL vs. 3.4 ± 0.3 cells/μL, P = 0.028; Fig. 2A ). When patients with AMD were divided into active and stable groups, there was a statistically significantly increase of CD34+HSC in patients with active AMD versus control subjects (control: 3.4 ± 0.3 cells/μL, stable: 4.1 ± 0.2 cells/μL, active: 5.1 ± 0.5 cells/μL, control versus active P = 0.019, stable versus active P = 0.23, Fig. 2B ). And increases in CD34+HSC levels were related to the interval from the last CNV progression (≥12 months: 4.0 ± 0.3 cells/μL, 6–12 months: 4.2 ± 0.4 cells/μL, 1–3 months: 4.6 ± 0.5 cells/μL, <1 month: 6.0 ± 0.9 cells/μL, ≥12 months vs. <1 month: P = 0.044, 1–3 months vs. <1 month: P = 0.057; Fig. 2C ). It should be noted that the increase in CD34+ HSCs with CNV activity was observed irrespective of the history of systemic disease, including diabetes, cardiovascular diseases, cerebrovascular diseases cancer, anticoagulant medication, or statin medication that may affect the number of circulating HSCs. Figures 2Dillustrates data of CD34+ HSCs (n = 60) in patients without systemic diseases. The increases in the number of cells were unaffected by the presence of systemic diseases, and, of note, the difference in the number of CD34+HSCs became more distinct and significant when patients with systemic diseases were removed (CD34+ HSCs; control: 3.7 ± 0.5 cells/μL, stable: 3.8 ± 0.3 cells/μL, active: 5.5 ± 0.7 cells/μL, stable versus active: P = 0.049; Fig. 2D ). 
The number of circulating CD34+ HSCs seemed unaffected by the size or laterality of CNV (size; <3000 μm: 4.7 ± 0.4 cells/μL vs. ≥3000 μm: 4.4 ± 0.4 cells/μL, P = 0.38, Fig. 2E ; and laterality; unilateral: 4.5 ± 0.3 cells/μL versus bilateral: 4.8 ± 0.5 cells/μL, P = 0.64; Fig. 2F ). 
By univariate analysis for the entire cohort, gender, smoking, AMD activity, and bilateral CNV correlated with the number of CD34+ HSCs (Table 2) . By multivariate analysis, gender and AMD activity were significant independent predictors of the number of CD34+ HSCs, whereas hypertension was the only significant independent predictor of a reduced number of CD34+ HSCs (Table 3) . To confirm whether gender or presence of hypertension affected our results, we analyzed the correlation of CNV activity and CD34+HSC in male patients without hypertension. The increase of HSC in patients with active CNV was still significant, even in this setting (P = 0.03, data not shown). 
Serum Cytokine Levels in Patients with Active or Stable States of Neovascular AMD
Several reports have suggested mobilization of HSCs can be achieved by the induction of specific serum cytokines. 20 21 22 To identify possible cytokines that may control HSC mobilization in neovascular AMD, we measured several serum cytokines that have been reported to mobilize HSCs (Fig. 3) . We found that serum Epo levels were higher in the active group than in the stable group (mean, 14.98 ± 1.45 mIU/mL vs. 11.97 ± 1.10 mIU/mL, P = 0.27; Fig. 3A ), although the difference was not statistically significant. The serum Epo level and number of circulating CD34+ HSCs, however, correlated positively (r = 0.47, P = 0.0021; Fig. 3E ). It should be noted that the increased serum Epo levels (range, 3.62–37.76 mIU/mL) were not very different from normal levels (8–30 mIU/mL). 
VEGF (stable: 325.5 ± 55.3 pg/mL vs. active: 218.4 ± 59.3 pg/mL, P = 0.07, Fig. 3B ), SDF-1 (stable: 2214.9 ± 130.7 pg/mL vs. active: 2212.2 ± 89.2 pg/mL, P = 0.71; Fig. 3C ), and Ang-1 (stable: 23,951 ± 3,158 pg/mL versus active: 19,444 ± 2,575 pg/mL, P = 0.28; Fig. 3D ) levels were not different between the active and stable CNV groups. Although the serum VEGF and SDF-1 levels did not correlate with the number of circulating CD34+ HSCs (Figs. 3F 3G) , the serum Ang-1 level correlated inversely with the number of circulating CD34+ HSCs (r = −0.40, P = 0.010; Fig. 3H ). 
Functional Impairments of Circulating HSCs in Severe Neovascular AMD
Previous reports have shown that bone marrow–derived cells including circulating HSCs and endothelial progenitor cells (EPCs) are incorporated into the experimental CNV model, suggesting HSCs and EPCs induce and promote CNV formation. 5 6 To clarify the roles of HSCs in the formation of neovascular AMD, we measured functional activities of patients by using ex vivo culture assays, and investigated the association between HSC functions and clinical severity (Table 4) . Although CFU-ECs have been used in examining the function of EPCs, recent study suggest that CFU-ECs represent more the function of myeloid progenitor cells than that of EPCs. We measured HSC function by using CFU-EC (Fig. 4A) , as well as migration analysis. The CFU-EC reportedly decreases with age. 14 23 Therefore, we first examined samples from young and older healthy volunteers. We confirmed that an inverse correlation was observed between age with CFU-EC (r = −0.48, P = 0.01; n = 25; Fig. 4B ) and migration (r = −0.76, P < 0.001, n = 21; Fig. 4C ) in healthy control subjects. 
As shown in Figures 5A and 5B , CFU-EC and migration of cultured HSCs was the same between patients with AMD and age-matched control subjects. Unlike the number of circulating CD34+ HSCs, differences in CFU-ECs and migration was not observed between the active and stable neovascular AMD groups (data not shown). However, CFU-ECs in patients with large (≥3000 μm) CNV lesions was significantly lower than in patients with smaller (<3000 μm) lesions (21.5 ± 4.4 vs. 37.3 ± 6.3, P = 0.02; Fig. 5C ). Similarly, migration was 38% lower in patients with larger CNV than in patients with smaller CNV (165.5% ± 9.5% vs. 200.3% ± 22.6%, P = 0.08; Fig. 5D ). There was no statistically significant age difference between these groups. Furthermore, in bilaterally affected patients compared with unilaterally affected patients, both CFU-EC and migration were significantly lower (CFU-EC mean, 18.8 ± 4.8 vs. 33.2 ± 5.0, P = 0.02; Fig. 5E ; migration mean, 153.6% ± 8.0% vs. 193.0% ± 16.3%, P = 0.02; Fig. 5F ). 
Discussion
In the disease state, circulating HSCs reportedly have either a beneficial or detrimental effect. Studies on hindlimb ischemia and ischemic heart failure suggest that HSC recruitment to ischemic sites plays an important role in rescuing the lesioned eye, since the incorporated HSCs promote local angiogenesis and improve ischemic tissue function. 13 20 Atherosclerotic studies have proposed an alternate beneficial role for circulating HSCs. 12 24 Circulating HSCs are thought to have the capacity to repair vascular injuries. The injured endothelial monolayer is regenerated by circulating EPCs, accelerating reendothelialization, and limiting atherosclerotic lesion formation. Moreover, EPC impairment by risk factors, such as age and diabetes, may contribute to atherogenesis and atherosclerotic disease progression. In contrast, circulating HSCs’ angiogenic function in cancer research is thought to be detrimental, since angiogenesis is a major part of the pathogenesis of cancer progression. 3 Similarly, the role of circulating HSCs in CNV formation in neovascular AMD has been considered to include stimulating lesion growth, 25 since angiogenesis is the most important factor in CNV. All current and new therapeutic approaches for treating CNV, including laser treatment, photodynamic therapy, and anti-VEGF therapy, attempt to stop neovascularization. 
To investigate the actual role of circulating HSCs in the formation or progression of CNV in AMD, we examined the number and function of these cells using current methodology. We found the number of circulating CD34+ HSCs increased in the patients with active CNV compared with those with stable CNV and control subjects. Also, the functions of circulating HSCs (CFU-EC and migration) decreased in patients with larger or bilateral CNV involvement. Moreover, these results were not associated with conditions that may affect the number or function of HSCs. This suggests an active CNV lesion itself can mobilize HSCs from bone marrow into the circulation. Those HSCs may be recruited to the CNV and have an important role in the formation and progression of CNV, as reported. Our findings of abnormal functions of circulating HSCs and how they may be related to progression of CNV support the hypothesis that circulating HSCs protect rather than promote CNV formation, as previously suggested. 9  
If circulating HSCs protect against CNV formation, what is the cellular mechanism? Unfortunately, we could not identify the specific cell types and mechanisms that may be involved. Based on our findings, there is a possibility that the function rather than the recruitment of HSCs is the key in the progression of CNV, since there was no significant correlation between the number of circulating CD34+ HSCs and severity of CNV in our patients. HSCs may play only a small role in the initiation of CNV because the functional activities were similar between patients with AMD and control subjects (Figs. 5A 5B) . The recruited HSCs/EPCs at the site of CNV formation may play a role in the vessel maturation that results in reduction of CNV size, because endothelial repair capacity of these cells were reported. 12 24 When the functions of HSCs/EPCs are decreased, they cannot perform the expected role at the sites of angiogenesis and may result in immature vascular formation. This dysfunctional vasculature may cause sustained exudative changes and CNV progression in severe AMD cases. Other cell types, including smooth muscle cells, microglia, macrophages, and RPE are also major components of CNV tissue and can originate from bone marrow HSCs. 9 26 27 28 29 Some investigators consider CNV to be a type of wound-healing process, of which angiogenesis is just one component. 30 Thus, the decreased functions of HSCs may also cause the dysfunction of these cells in CNV. Yoder et al. 31 recently reported that CFU-EC may not represent well a function of EPC, but a function of myeloid progenitor cells. If the same is true, our functional analysis results suggest the importance of myeloid lineage cells in the formation of CNV. It can also be speculated that impairment of the function of circulating HSCs causes reduced wound healing and enables CNV to progress. Although there are technical difficulties in the separation and measurement of bone marrow–derived progenitors, further functional analyses are ongoing. 
Our results also suggest that a new therapeutic approach, where functionally active circulating HSCs are important in preventing CNV progression, is necessary. In the experimental CNV model, we could reduce the size of the CNV lesion by functional recovery of circulating HSCs via bone marrow transplantation, which could change the bone marrow of aged mice to that of young donor mice without changing ocular factors (manuscript in preparation). Therefore, functional maintenance or improvement of circulating HSCs using systemic cytokine injection therapy, which enables promoting the functions, 32 could be a new therapeutic target in the prevention of CNV progression. Giving up smoking may have some benefit, because smoking, a proven environmental risk factor in neovascular AMD, 33 is known to decrease EPC function. 34  
In the present study, the circulating HSCs increased with the activity of the CNV lesion, regardless of systemic disease, suggesting that an active CNV lesion may signal mobilization of CD34+ HSCs from the bone marrow into the peripheral circulation. It is surprising that changes of very small (less than several millimeters in diameter) lesions can control the systemic number of bone marrow–derived stem cells. Although the mechanism of mobilization of CD34+ HSCs into circulation has not been determined, we found that serum Epo or Ang-1 may play a role in AMD. Epo is known to have mobilization capacity of HSCs, 21 35 and our results (Figs. 3A 3E)are consistent with these previous reports. However, which cells produce Epo in active CNV lesions should be elucidated. On the other hand, serum Ang-1 level correlated inversely with the number of circulating HSCs in patients with neovascular AMD (Fig. 3H) . Ang-1 is an angiogenic growth factor and contributes to vessel maturation and stabilization in ocular angiogenesis. In addition, some researchers report that Ang-1 can mobilize ability HSCs. 36 Because our results conflict with such reports, further study of HSCs reaction to Ang-1 is required. SDF-1 is a chemoattractant protein that plays a central role in the homing process of bone marrow–derived stem cells and is expressed in RPE cells after injury. 37 38 In our study series, however, the serum SDF-1 level did not vary between patients with active and stable CNV (Fig. 3C)and had no correlation with the number of circulating CD34+ HSCs (Fig. 3G) . This finding suggests that SDF-1 may not work as a chemoattractant in formation of CNV. 
In conclusion, by analysis of the correlation of circulating HSCs with the detailed clinical characteristics of patients with neovascular AMD, we identified a possible systemic factor that has a significant impact on the formation of CNV. Circulating HSCs may be mobilized in the active state in CNV, and recruited cells may have a reparative or protective role against progression. This study, however, is cross-sectional, and many cellular mechanisms remain to be elucidated. Further intensive experiments, as well as prospective and longitudinal clinical studies, are necessary. 
 
Figure 1.
 
Quantification of CD34+ mononuclear cells by flow cytometry. (A) Lymphocyte and monocyte gate (R1) indicated on a dot plot of nucleic acid dye versus sidescatter (SSC). (B) On the CD45 PerCP versus SSC dot plot, dim CD45/low SSC population (R2) and fluorescent-dyed microbeads (R4) were gated. (C) CD34+ cells were gated on the nucleic acid dye versus CD34 PE dot plot; R3 gated off R1 and R2. (D) The indicated regions are used for the isotype control.
Figure 1.
 
Quantification of CD34+ mononuclear cells by flow cytometry. (A) Lymphocyte and monocyte gate (R1) indicated on a dot plot of nucleic acid dye versus sidescatter (SSC). (B) On the CD45 PerCP versus SSC dot plot, dim CD45/low SSC population (R2) and fluorescent-dyed microbeads (R4) were gated. (C) CD34+ cells were gated on the nucleic acid dye versus CD34 PE dot plot; R3 gated off R1 and R2. (D) The indicated regions are used for the isotype control.
Figure 2.
 
Mobilization of hematopoietic stem cells (CD34+) into the circulation in active stages of neovascular AMD. (A) Average number of peripheral CD34+ cells in age-matched healthy control subjects (n = 21) and patients with AMD (n = 81). (B) Average number of peripheral CD34+ cells in age-matched healthy control subjects (n = 21), stable AMD group (patients without progression of CNV within 6 months, n = 42), and active AMD group (patients with progression of CNV within 3 months, n = 39). (C) Association between the interval from the last CNV progression (≥12 months: n = 22, 6–12 months:n = 20, 1–3 months: n = 25, <1 month: n = 14) and the number of CD34+ cells in patients with AMD. (D) Average number of peripheral CD34+ cells in the control (n = 12), stable AMD (n = 26), and active AMD (n = 22) groups in patients without diabetes, cardiovascular disease, cerebrovascular disease, cancer, anticoagulant medication, or statin medication. (E) Comparison of CD34+ cell levels between patients with smaller CNV size (<3000 μm; n = 40) and those with larger CNV size (≥3000 μm;n = 41). (F) Comparison of CD34+ cell levels between unilateral CNV patients (n = 57) and patients with bilateral CNV (n = 24). Data are presented as the mean ± SEM.
Figure 2.
 
Mobilization of hematopoietic stem cells (CD34+) into the circulation in active stages of neovascular AMD. (A) Average number of peripheral CD34+ cells in age-matched healthy control subjects (n = 21) and patients with AMD (n = 81). (B) Average number of peripheral CD34+ cells in age-matched healthy control subjects (n = 21), stable AMD group (patients without progression of CNV within 6 months, n = 42), and active AMD group (patients with progression of CNV within 3 months, n = 39). (C) Association between the interval from the last CNV progression (≥12 months: n = 22, 6–12 months:n = 20, 1–3 months: n = 25, <1 month: n = 14) and the number of CD34+ cells in patients with AMD. (D) Average number of peripheral CD34+ cells in the control (n = 12), stable AMD (n = 26), and active AMD (n = 22) groups in patients without diabetes, cardiovascular disease, cerebrovascular disease, cancer, anticoagulant medication, or statin medication. (E) Comparison of CD34+ cell levels between patients with smaller CNV size (<3000 μm; n = 40) and those with larger CNV size (≥3000 μm;n = 41). (F) Comparison of CD34+ cell levels between unilateral CNV patients (n = 57) and patients with bilateral CNV (n = 24). Data are presented as the mean ± SEM.
Table 1.
 
Baseline Characteristics of the AMD Patients and Controls
Table 1.
 
Baseline Characteristics of the AMD Patients and Controls
Characteristics Control (n = 21) Stable AMD (n = 42) Active AMD (n = 39) P
Sex, n (%)
 Male 13 (62) 23 (55) 30 (77) NS
 Female 8 (38) 19 (45) 9 (23) NS
Age
 Mean (y) 69.6 ± 8.6 73.2 ± 7.8 71.5 ± 7.7 NS
 Median, y (range) 71 (56–82) 74 (50–90) 73 (54–83)
 50–64 y, n (%) 6 (29) 4 (10) 10 (25)
 65–74 y, n (%) 8 (38) 18 (43) 12 (31)
 75–84 y, n (%) 7 (33) 19 (45) 17 (44)
 ≥85 y, n (%) 0 (0) 1 (2) 0 (0)
Angiographic subtype of CNV, n (%)
 Predominantly classic CNV 7 (17) 8 (21) NS
 Minimally classic CNV 7 (17) 5 (13) NS
 Occult CNV 28 (66) 26 (66)
Size of lesion (μm) 3592 ± 2034 3221 ± 1477 NS
Laterality of CNV
 Bilateral 12 (29) 12 (31) NS
 Unilateral 30 (71) 27 (69) NS
History of ocular surgery or laser treatment, n (%)
 Before 6 months ago 1 (5) 18 (43) 12 (31) 0.008
 Within past 6 months 0 (0) 0 (0) 0 (0)
Best-corrected visual acuity (logMAR)
 Worse eye
  Mean 0.51 ± 0.61 0.73 ± 0.56 0.59 ± 0.44 NS
  Median 0.3 0.52 0.52
  Range −0.18–2.00 −0.08–2.00 −0.08–2.00
 Better eye
  Mean 0.09 ± 0.40 0.09 ± 0.35 0.16 ± 0.46 NS
  Median 0.05 0 −0.08
  Range −0.18–1.70 −0.18–1.70 −0.18–1.52
Systemic disease, n (%)
 Hypertension 6 (29) 14 (33) 18 (46) NS
 Diabetes Mellitus 5 (24) 3 (7) 8 (21) NS
 Hyperlipidemia 4 (19) 6 (14) 4 (10) NS
 History of cardiovascular disease 4 (19) 7 (17) 8 (21) NS
 History of cerebrovascular disease 1 (5) 0 (0) 1 (3) NS
 History of cancer 1 (5) 3 (7) 2 (5) NS
Anticoagulant medication, n (%) 1 (5) 6 (14) 8 (21) NS
Statin medication, n (%) 3 (14) 4 (10) 3 (8) NS
History of smoking, n (%) 6 (29) 16 (38) 20 (51) NS
Table 2.
 
Univariate Correlation between CD34+ HSCs and Risk Factors or Clinical Conditions
Table 2.
 
Univariate Correlation between CD34+ HSCs and Risk Factors or Clinical Conditions
Characteristics ρ P
Risk factors
 Age −0.076 0.444
 Sex (male) 0.274 0.006
 History of smoking 0.230 0.021
 Systemic disease
  Hypertension −0.116 0.245
  Diabetes Mellitus −0.060 0.544
  Hyperlipidemia −0.025 0.800
  History of cardiovascular disease 0.063 0.538
  History of cerebrovascular disease −0.065 0.515
  History of cancer 0.091 0.363
Clinical conditions
  Anticoagulant medication 0.112 0.259
  Statin medication −0.030 0.761
AMD conditions
 Activity of AMD 0.238 0.017
 Size of lesion (μm) 0.116 0.244
 Laterality of CNV (bilateral) 0.203 0.042
Table 3.
 
Multiple Linear Regression Analyses between CD34+ HSCs and Risk Factors or Clinical Conditions
Table 3.
 
Multiple Linear Regression Analyses between CD34+ HSCs and Risk Factors or Clinical Conditions
Characteristics β Coefficient (r 2 = 0.25) P
Risk factors
 Age 0.020 0.843
 Sex (male) 0.239 0.042
 History of smoking 0.215 0.070
 Systemic disease
  Hypertension −0.217 0.037
  Diabetes Mellitus −0.105 0.313
  Hyperlipidemia 0.125 0.482
  History of cardiovascular disease −0.134 0.264
  History of cerebrovascular disease −0.085 0.394
  History of cancer 0.079 0.423
Clinical conditions
 Anticoagulant medication 0.122 0.297
 Statin medication −0.008 0.964
AMD conditions
 Activity of AMD 0.254 0.049
 Size of lesion (μm) −0.177 0.166
 Laterality of CNV (bilateral) 0.110 0.450
Significance (ANOVA) 0.020
Figure 3.
 
Serum cytokine measurements in patients with neovascular AMD. (A) Serum erythropoietin (Epo) levels in stable (n = 17) and active (n = 27) AMD. (B) Serum VEGF levels in stable (n = 23) and active (n = 20) AMD. (C) SDF-1α levels in stable (n = 17) and active (n = 26) AMD. (D) Serum Ang-1 levels in stable (n = 16) and active (n = 26) AMD. (E) Simple correlation between serum Epo level and the number of CD34+ cells. (F) Simple correlation between serum VEGF level and the number of CD34+ cells. (G) Simple correlation between serum SDF-1α level and the number of CD34+ cells. (H) Simple correlation between serum Ang-1 level and the number of CD34+ cells.
Figure 3.
 
Serum cytokine measurements in patients with neovascular AMD. (A) Serum erythropoietin (Epo) levels in stable (n = 17) and active (n = 27) AMD. (B) Serum VEGF levels in stable (n = 23) and active (n = 20) AMD. (C) SDF-1α levels in stable (n = 17) and active (n = 26) AMD. (D) Serum Ang-1 levels in stable (n = 16) and active (n = 26) AMD. (E) Simple correlation between serum Epo level and the number of CD34+ cells. (F) Simple correlation between serum VEGF level and the number of CD34+ cells. (G) Simple correlation between serum SDF-1α level and the number of CD34+ cells. (H) Simple correlation between serum Ang-1 level and the number of CD34+ cells.
Table 4.
 
Patient Characteristics in Functional Assays of EPCs
Table 4.
 
Patient Characteristics in Functional Assays of EPCs
Characteristics Control (n = 21) AMD (n = 46) P Lesion Size <3000 μm (n = 24) Lesion Size ≥3000 μm (n = 22) P
Sex, n (%)
 Male 13 (62) 32 (76) NS 14 (58) 18 (82) NS
 Female 8 (38) 14 (24) NS 10 (42) 4 (18) NS
Age
 Mean 69.6 ± 8.6 73.2 ± 8.5 NS 71.8 ± 8.7 74.0 ± 8.0 NS
 Median (range) 71 (56–82) 74 (50–87) 72 (50–87) 75 (54–83)
 50–64 y, n (%) 6 (29) 6 (13) 5 (21) 1 (5)
 65–74 y, n (%) 8 (38) 21 (46) 11 (46) 10 (45)
 75–84 y, n (%) 7 (33) 18 (39) 7 (29) 11 (50)
 ≥85 y, n (%) 0 (0) 1 (2) 1 (4) 0 (0)
Angiographic subtype of lesion, n (%)
 Predominantly classic CNV 10 (21) 5 (21) 5 (23) NS
 Minimally classic CNV 5 (11) 0 (0) 5 (23) 0.02
 Occult with no classic CNV 31 (67) 19 (79) 12 (55) NS
Size of lesion (μm) 4057 ± 2675 2078 ± 553 6216 ± 2374 <0.001
Laterality of CNV
 Unilateral 35 (76) 24 (100) 11 (50) <0.001
 Bilateral 11 (24) 0 (0) 11 (50) <0.001
History of ocular surgery or laser treatment, n (%)
 Within last 6 months 0 (0) 0 (0) 0 (0) 0 (0)
Best-corrected visual acuity (logMAR)
 Worse eye
  Mean 0.51 ± 0.61 0.73 ± 0.55 <0.001 0.45 ± 0.39 1.04 ± 0.53 <0.001
  Median 0.30 0.70 0.30 1.00
  Range −0.18–2.00 0.00–2.00 0.00–1.52 0.30–2.00
Better eye
  Mean 0.09 ± 0.40 0.16 ± 0.41 NS −0.030 ± 0.19 0.36 ± 0.49 <0.001
  Median 0.30 −0.079 −0.079 0.16
  Range −0.18–1.70 −0.18–1.52 −0.18–0.70 −0.18–1.52
Systemic disease, n (%)
 Hypertension 6 (29) 22 (48) NS 10 (42) 12 (55) NS
 Diabetes Mellitus 5 (24) 6 (13) NS 2 (8) 4 (18) NS
 Hyperlipidemia 4 (19) 8 (17) NS 3 (13) 5 (23) NS
 History of cardiovascular disease 4 (19) 11 (24) NS 3 (13) 8 (36) NS
 History of cerebrovascular disease 1 (5) 4 (9) NS 2 (8) 2 (9) NS
Anticoagulant medication, n (%) 1 (5) 7 (15) NS 4 (17) 3 (14) NS
Statin medication, n (%) 3 (14) 1 (2) NS 0 (0) 1 (5) NS
History of smoking, n (%) 6 (29) 26 (57) 0.04 12 (50) 14 (64) NS
Figure 4.
 
Age-dependent decrease in function of circulating progenitor cells of healthy control subjects. The functional activities of cultured HSCs include CFU-EC and migration (data presented as the percentage of relative fluorescent units with 10% fetal bovine serum to without serum). (A) A colony derived from hematopoietic stem cells. (B) Inverted correlation of age and CFU-ECs. (C) Age-dependent decrease in migration of cultured HSCs.
Figure 4.
 
Age-dependent decrease in function of circulating progenitor cells of healthy control subjects. The functional activities of cultured HSCs include CFU-EC and migration (data presented as the percentage of relative fluorescent units with 10% fetal bovine serum to without serum). (A) A colony derived from hematopoietic stem cells. (B) Inverted correlation of age and CFU-ECs. (C) Age-dependent decrease in migration of cultured HSCs.
Figure 5.
 
Decreased functional activities of HSCs of patients with severe CNV in AMD. (A, B) Comparison of CFU-ECs and migration between age-matched healthy control subjects (n = 21) and patients with neovascular AMD (n = 46). (C, D) Comparison of CFU-ECs and migration between patients with smaller CNV size (<3000 μm; n = 24) and those with larger CNV size (≥3000 μm; n = 22). (E, F) Comparison of CFU-ECs and migration between patients with unilateral (n = 35) and those with bilateral (n = 11) CNV. Data are presented as the mean ± SEM.
Figure 5.
 
Decreased functional activities of HSCs of patients with severe CNV in AMD. (A, B) Comparison of CFU-ECs and migration between age-matched healthy control subjects (n = 21) and patients with neovascular AMD (n = 46). (C, D) Comparison of CFU-ECs and migration between patients with smaller CNV size (<3000 μm; n = 24) and those with larger CNV size (≥3000 μm; n = 22). (E, F) Comparison of CFU-ECs and migration between patients with unilateral (n = 35) and those with bilateral (n = 11) CNV. Data are presented as the mean ± SEM.
The authors appreciate the technical advice and support of colleagues Norimoto Gotoh, Hiroko Hizaki, Yuko Sasahara, Kaori Asamoto, Kayo Nishida, and Junko Nakamura. 
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Figure 1.
 
Quantification of CD34+ mononuclear cells by flow cytometry. (A) Lymphocyte and monocyte gate (R1) indicated on a dot plot of nucleic acid dye versus sidescatter (SSC). (B) On the CD45 PerCP versus SSC dot plot, dim CD45/low SSC population (R2) and fluorescent-dyed microbeads (R4) were gated. (C) CD34+ cells were gated on the nucleic acid dye versus CD34 PE dot plot; R3 gated off R1 and R2. (D) The indicated regions are used for the isotype control.
Figure 1.
 
Quantification of CD34+ mononuclear cells by flow cytometry. (A) Lymphocyte and monocyte gate (R1) indicated on a dot plot of nucleic acid dye versus sidescatter (SSC). (B) On the CD45 PerCP versus SSC dot plot, dim CD45/low SSC population (R2) and fluorescent-dyed microbeads (R4) were gated. (C) CD34+ cells were gated on the nucleic acid dye versus CD34 PE dot plot; R3 gated off R1 and R2. (D) The indicated regions are used for the isotype control.
Figure 2.
 
Mobilization of hematopoietic stem cells (CD34+) into the circulation in active stages of neovascular AMD. (A) Average number of peripheral CD34+ cells in age-matched healthy control subjects (n = 21) and patients with AMD (n = 81). (B) Average number of peripheral CD34+ cells in age-matched healthy control subjects (n = 21), stable AMD group (patients without progression of CNV within 6 months, n = 42), and active AMD group (patients with progression of CNV within 3 months, n = 39). (C) Association between the interval from the last CNV progression (≥12 months: n = 22, 6–12 months:n = 20, 1–3 months: n = 25, <1 month: n = 14) and the number of CD34+ cells in patients with AMD. (D) Average number of peripheral CD34+ cells in the control (n = 12), stable AMD (n = 26), and active AMD (n = 22) groups in patients without diabetes, cardiovascular disease, cerebrovascular disease, cancer, anticoagulant medication, or statin medication. (E) Comparison of CD34+ cell levels between patients with smaller CNV size (<3000 μm; n = 40) and those with larger CNV size (≥3000 μm;n = 41). (F) Comparison of CD34+ cell levels between unilateral CNV patients (n = 57) and patients with bilateral CNV (n = 24). Data are presented as the mean ± SEM.
Figure 2.
 
Mobilization of hematopoietic stem cells (CD34+) into the circulation in active stages of neovascular AMD. (A) Average number of peripheral CD34+ cells in age-matched healthy control subjects (n = 21) and patients with AMD (n = 81). (B) Average number of peripheral CD34+ cells in age-matched healthy control subjects (n = 21), stable AMD group (patients without progression of CNV within 6 months, n = 42), and active AMD group (patients with progression of CNV within 3 months, n = 39). (C) Association between the interval from the last CNV progression (≥12 months: n = 22, 6–12 months:n = 20, 1–3 months: n = 25, <1 month: n = 14) and the number of CD34+ cells in patients with AMD. (D) Average number of peripheral CD34+ cells in the control (n = 12), stable AMD (n = 26), and active AMD (n = 22) groups in patients without diabetes, cardiovascular disease, cerebrovascular disease, cancer, anticoagulant medication, or statin medication. (E) Comparison of CD34+ cell levels between patients with smaller CNV size (<3000 μm; n = 40) and those with larger CNV size (≥3000 μm;n = 41). (F) Comparison of CD34+ cell levels between unilateral CNV patients (n = 57) and patients with bilateral CNV (n = 24). Data are presented as the mean ± SEM.
Figure 3.
 
Serum cytokine measurements in patients with neovascular AMD. (A) Serum erythropoietin (Epo) levels in stable (n = 17) and active (n = 27) AMD. (B) Serum VEGF levels in stable (n = 23) and active (n = 20) AMD. (C) SDF-1α levels in stable (n = 17) and active (n = 26) AMD. (D) Serum Ang-1 levels in stable (n = 16) and active (n = 26) AMD. (E) Simple correlation between serum Epo level and the number of CD34+ cells. (F) Simple correlation between serum VEGF level and the number of CD34+ cells. (G) Simple correlation between serum SDF-1α level and the number of CD34+ cells. (H) Simple correlation between serum Ang-1 level and the number of CD34+ cells.
Figure 3.
 
Serum cytokine measurements in patients with neovascular AMD. (A) Serum erythropoietin (Epo) levels in stable (n = 17) and active (n = 27) AMD. (B) Serum VEGF levels in stable (n = 23) and active (n = 20) AMD. (C) SDF-1α levels in stable (n = 17) and active (n = 26) AMD. (D) Serum Ang-1 levels in stable (n = 16) and active (n = 26) AMD. (E) Simple correlation between serum Epo level and the number of CD34+ cells. (F) Simple correlation between serum VEGF level and the number of CD34+ cells. (G) Simple correlation between serum SDF-1α level and the number of CD34+ cells. (H) Simple correlation between serum Ang-1 level and the number of CD34+ cells.
Figure 4.
 
Age-dependent decrease in function of circulating progenitor cells of healthy control subjects. The functional activities of cultured HSCs include CFU-EC and migration (data presented as the percentage of relative fluorescent units with 10% fetal bovine serum to without serum). (A) A colony derived from hematopoietic stem cells. (B) Inverted correlation of age and CFU-ECs. (C) Age-dependent decrease in migration of cultured HSCs.
Figure 4.
 
Age-dependent decrease in function of circulating progenitor cells of healthy control subjects. The functional activities of cultured HSCs include CFU-EC and migration (data presented as the percentage of relative fluorescent units with 10% fetal bovine serum to without serum). (A) A colony derived from hematopoietic stem cells. (B) Inverted correlation of age and CFU-ECs. (C) Age-dependent decrease in migration of cultured HSCs.
Figure 5.
 
Decreased functional activities of HSCs of patients with severe CNV in AMD. (A, B) Comparison of CFU-ECs and migration between age-matched healthy control subjects (n = 21) and patients with neovascular AMD (n = 46). (C, D) Comparison of CFU-ECs and migration between patients with smaller CNV size (<3000 μm; n = 24) and those with larger CNV size (≥3000 μm; n = 22). (E, F) Comparison of CFU-ECs and migration between patients with unilateral (n = 35) and those with bilateral (n = 11) CNV. Data are presented as the mean ± SEM.
Figure 5.
 
Decreased functional activities of HSCs of patients with severe CNV in AMD. (A, B) Comparison of CFU-ECs and migration between age-matched healthy control subjects (n = 21) and patients with neovascular AMD (n = 46). (C, D) Comparison of CFU-ECs and migration between patients with smaller CNV size (<3000 μm; n = 24) and those with larger CNV size (≥3000 μm; n = 22). (E, F) Comparison of CFU-ECs and migration between patients with unilateral (n = 35) and those with bilateral (n = 11) CNV. Data are presented as the mean ± SEM.
Table 1.
 
Baseline Characteristics of the AMD Patients and Controls
Table 1.
 
Baseline Characteristics of the AMD Patients and Controls
Characteristics Control (n = 21) Stable AMD (n = 42) Active AMD (n = 39) P
Sex, n (%)
 Male 13 (62) 23 (55) 30 (77) NS
 Female 8 (38) 19 (45) 9 (23) NS
Age
 Mean (y) 69.6 ± 8.6 73.2 ± 7.8 71.5 ± 7.7 NS
 Median, y (range) 71 (56–82) 74 (50–90) 73 (54–83)
 50–64 y, n (%) 6 (29) 4 (10) 10 (25)
 65–74 y, n (%) 8 (38) 18 (43) 12 (31)
 75–84 y, n (%) 7 (33) 19 (45) 17 (44)
 ≥85 y, n (%) 0 (0) 1 (2) 0 (0)
Angiographic subtype of CNV, n (%)
 Predominantly classic CNV 7 (17) 8 (21) NS
 Minimally classic CNV 7 (17) 5 (13) NS
 Occult CNV 28 (66) 26 (66)
Size of lesion (μm) 3592 ± 2034 3221 ± 1477 NS
Laterality of CNV
 Bilateral 12 (29) 12 (31) NS
 Unilateral 30 (71) 27 (69) NS
History of ocular surgery or laser treatment, n (%)
 Before 6 months ago 1 (5) 18 (43) 12 (31) 0.008
 Within past 6 months 0 (0) 0 (0) 0 (0)
Best-corrected visual acuity (logMAR)
 Worse eye
  Mean 0.51 ± 0.61 0.73 ± 0.56 0.59 ± 0.44 NS
  Median 0.3 0.52 0.52
  Range −0.18–2.00 −0.08–2.00 −0.08–2.00
 Better eye
  Mean 0.09 ± 0.40 0.09 ± 0.35 0.16 ± 0.46 NS
  Median 0.05 0 −0.08
  Range −0.18–1.70 −0.18–1.70 −0.18–1.52
Systemic disease, n (%)
 Hypertension 6 (29) 14 (33) 18 (46) NS
 Diabetes Mellitus 5 (24) 3 (7) 8 (21) NS
 Hyperlipidemia 4 (19) 6 (14) 4 (10) NS
 History of cardiovascular disease 4 (19) 7 (17) 8 (21) NS
 History of cerebrovascular disease 1 (5) 0 (0) 1 (3) NS
 History of cancer 1 (5) 3 (7) 2 (5) NS
Anticoagulant medication, n (%) 1 (5) 6 (14) 8 (21) NS
Statin medication, n (%) 3 (14) 4 (10) 3 (8) NS
History of smoking, n (%) 6 (29) 16 (38) 20 (51) NS
Table 2.
 
Univariate Correlation between CD34+ HSCs and Risk Factors or Clinical Conditions
Table 2.
 
Univariate Correlation between CD34+ HSCs and Risk Factors or Clinical Conditions
Characteristics ρ P
Risk factors
 Age −0.076 0.444
 Sex (male) 0.274 0.006
 History of smoking 0.230 0.021
 Systemic disease
  Hypertension −0.116 0.245
  Diabetes Mellitus −0.060 0.544
  Hyperlipidemia −0.025 0.800
  History of cardiovascular disease 0.063 0.538
  History of cerebrovascular disease −0.065 0.515
  History of cancer 0.091 0.363
Clinical conditions
  Anticoagulant medication 0.112 0.259
  Statin medication −0.030 0.761
AMD conditions
 Activity of AMD 0.238 0.017
 Size of lesion (μm) 0.116 0.244
 Laterality of CNV (bilateral) 0.203 0.042
Table 3.
 
Multiple Linear Regression Analyses between CD34+ HSCs and Risk Factors or Clinical Conditions
Table 3.
 
Multiple Linear Regression Analyses between CD34+ HSCs and Risk Factors or Clinical Conditions
Characteristics β Coefficient (r 2 = 0.25) P
Risk factors
 Age 0.020 0.843
 Sex (male) 0.239 0.042
 History of smoking 0.215 0.070
 Systemic disease
  Hypertension −0.217 0.037
  Diabetes Mellitus −0.105 0.313
  Hyperlipidemia 0.125 0.482
  History of cardiovascular disease −0.134 0.264
  History of cerebrovascular disease −0.085 0.394
  History of cancer 0.079 0.423
Clinical conditions
 Anticoagulant medication 0.122 0.297
 Statin medication −0.008 0.964
AMD conditions
 Activity of AMD 0.254 0.049
 Size of lesion (μm) −0.177 0.166
 Laterality of CNV (bilateral) 0.110 0.450
Significance (ANOVA) 0.020
Table 4.
 
Patient Characteristics in Functional Assays of EPCs
Table 4.
 
Patient Characteristics in Functional Assays of EPCs
Characteristics Control (n = 21) AMD (n = 46) P Lesion Size <3000 μm (n = 24) Lesion Size ≥3000 μm (n = 22) P
Sex, n (%)
 Male 13 (62) 32 (76) NS 14 (58) 18 (82) NS
 Female 8 (38) 14 (24) NS 10 (42) 4 (18) NS
Age
 Mean 69.6 ± 8.6 73.2 ± 8.5 NS 71.8 ± 8.7 74.0 ± 8.0 NS
 Median (range) 71 (56–82) 74 (50–87) 72 (50–87) 75 (54–83)
 50–64 y, n (%) 6 (29) 6 (13) 5 (21) 1 (5)
 65–74 y, n (%) 8 (38) 21 (46) 11 (46) 10 (45)
 75–84 y, n (%) 7 (33) 18 (39) 7 (29) 11 (50)
 ≥85 y, n (%) 0 (0) 1 (2) 1 (4) 0 (0)
Angiographic subtype of lesion, n (%)
 Predominantly classic CNV 10 (21) 5 (21) 5 (23) NS
 Minimally classic CNV 5 (11) 0 (0) 5 (23) 0.02
 Occult with no classic CNV 31 (67) 19 (79) 12 (55) NS
Size of lesion (μm) 4057 ± 2675 2078 ± 553 6216 ± 2374 <0.001
Laterality of CNV
 Unilateral 35 (76) 24 (100) 11 (50) <0.001
 Bilateral 11 (24) 0 (0) 11 (50) <0.001
History of ocular surgery or laser treatment, n (%)
 Within last 6 months 0 (0) 0 (0) 0 (0) 0 (0)
Best-corrected visual acuity (logMAR)
 Worse eye
  Mean 0.51 ± 0.61 0.73 ± 0.55 <0.001 0.45 ± 0.39 1.04 ± 0.53 <0.001
  Median 0.30 0.70 0.30 1.00
  Range −0.18–2.00 0.00–2.00 0.00–1.52 0.30–2.00
Better eye
  Mean 0.09 ± 0.40 0.16 ± 0.41 NS −0.030 ± 0.19 0.36 ± 0.49 <0.001
  Median 0.30 −0.079 −0.079 0.16
  Range −0.18–1.70 −0.18–1.52 −0.18–0.70 −0.18–1.52
Systemic disease, n (%)
 Hypertension 6 (29) 22 (48) NS 10 (42) 12 (55) NS
 Diabetes Mellitus 5 (24) 6 (13) NS 2 (8) 4 (18) NS
 Hyperlipidemia 4 (19) 8 (17) NS 3 (13) 5 (23) NS
 History of cardiovascular disease 4 (19) 11 (24) NS 3 (13) 8 (36) NS
 History of cerebrovascular disease 1 (5) 4 (9) NS 2 (8) 2 (9) NS
Anticoagulant medication, n (%) 1 (5) 7 (15) NS 4 (17) 3 (14) NS
Statin medication, n (%) 3 (14) 1 (2) NS 0 (0) 1 (5) NS
History of smoking, n (%) 6 (29) 26 (57) 0.04 12 (50) 14 (64) NS
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