Objective
To report in African Americans with type 1 diabetes the association of single-nucleotide polymorphisms in 193 candidate genes with diabetic retinopathy (DR) and/or its progression.
Methods
A custom panel of 1536 single-nucleotide polymorphisms located on 193 candidate genes for DR was genotyped in 437 African Americans with type 1 diabetes who participated in the New Jersey 725 study. Clinical evaluations at baseline and follow-up examinations included structured clinical interview, ocular examination, 7-field stereoscopic fundus photographs, and blood pressure measurements. Severity of DR was determined via masked grading of fundus photographs. Biological evaluations included blood and urine assays.
Results
Single-nucleotide polymorphisms in 13 candidate genes for DR involved in glucose metabolism, angiogenesis, inflammation, neurotransmission, hypertension, and retinal development were significantly associated with the prevalence of severe DR. Three of these genes were also significantly associated with progression of DR. Adjusting for sex, duration of diabetes, glycosylated hemoglobin, systemic hypertension, and total cholesterol did not alter the results.
Conclusions
Our data support the role of genetic factors to account for severity and/or progression of DR in African Americans with type 1 diabetes and to identify several prime genes that likely contribute to the risk of DR.
Despite effective treatments for the severe forms of diabetic retinopathy (DR), the disease remains the leading cause of blindness in 20- to 64-year-old persons with diabetes mellitus (DM) in the United States.1,2 In this group, proliferative DR (PDR) and macular edema are the 2 main causes of visual loss.3 Environmental and clinical risk factors for PDR have been reported previously for various populations with type 1 DM and include longer duration of diabetes, poor glycemic control, systemic hypertension, and proteinuria.3,4 These, however, account for only a portion of the severe forms of the disease.5 Familial aggregation of severe DR, independent of the known clinical risk factors, has been reported in patients with DM.6-11 Thus, it is likely that genes, possibly combined with environmental factors, account for some of the variance in DR severity.12-14
While the pathophysiology of DR remains unclear, a number of metabolic pathways and their associated genes have been implicated.13-16 Such candidate genes include those involved in glucose metabolism and transport, synthesis and degradation of basement membranes, angiogenesis, inflammation, blood pressure regulation, coagulation, and neurotransmission. Previously published studies of these candidate genes for DR, however, have yielded conflicting data, most likely the result of many studies having involved small sample sizes and poorly characterized phenotypes.11,14,16-19 Other potential problems may include population stratification and the possible involvement of more than 1 gene.
We previously assembled (baseline), examined (baseline), and reexamined (6-year follow-up) a large, geographically well-defined population of African Americans with diagnosed type 1 DM: the New Jersey 725.4,5,20,21 At each examination, patients' retinal status was well characterized using masked grading of the 7-field stereoscopic fundus photographs.22-24 Standard protocols were used to document diabetic complications and biological abnormalities. We found that clinical risk factors associated with either any progression of DR or progression to PDR accounted for only 27% of the variance in DR severity.5 Because our New Jersey 725 cohort provides a unique opportunity to examine genes associated with DR in African Americans with type 1 DM, we studied the associations between severe DR and/or its progression and polymorphisms in 193 candidate genes in this population.
The original cohort consisted of 725 African Americans with type 1 DM who participated in the New Jersey 725 study between 1993 and 1998.20 Patients with a discharge diagnosis of DM were identified from the New Jersey Hospital discharge data, which lists all patients who have been admitted to New Jersey hospitals. This computer-generated list includes demographic information about patients, including race. African Americans with diagnosed DM and treated with insulin before 30 years of age and who were currently taking insulin were further identified from a random review of 13 615 medical records. Exclusion criteria were type 2 DM, diagnosis after age 30 years, and maturity-onset diabetes of youth.25-27 Ethnicity was determined from the hospital record and later confirmed by self-identification. Patients were also asked to confirm that both of their parents were African American. Of the original cohort of 725 subjects, 508 participated in the 6-year follow-up examination between 1999 and 2004. At the 6-year follow-up, 25 of the 508 participants (4.9%) who were no longer receiving insulin were excluded from further analyses.21 Of the remaining 483 patients, blood was drawn for genetic studies in 337 patients at the time of the 6-year follow-up and in 82 patients who were subsequently recalled for blood draws between 2005 and 2006. An additional 18 African Americans with type 1 DM were also recruited for genetic studies using the same inclusion criteria as in the patients in the New Jersey 725 study.20 Thus, there were 437 patients available for genotyping.
Patients were examined in the Eye Clinic of University Hospital in Newark, New Jersey. Upon arrival, informed written consent was obtained from each study participant. Patients underwent a complete eye examination that included dilated retinal examination and 7-field stereoscopic Diabetic Retinopathy Study retinal photographs.22 Also obtained were height, weight, and blood pressure measurements. A structured clinical interview included detailed medical and ophthalmologic histories as well as sociodemographic factors and lifestyle variables. Previous ophthalmic medical records were obtained. Dates of all previous ophthalmologic procedures, including panretinal laser photocoagulation and/or pars plana vitrectomy for PDR were recorded. Venous blood was drawn for measurement of total glycosylated hemoglobin and high- and low-density lipoprotein cholesterol and total cholesterol. A 4-hour timed urine collection was obtained for measurement of albumin excretion rate and creatinuria. The institutional review board at the University of Medicine and Dentistry of New Jersey, New Jersey Medical School, Newark, approved the study.
Dr grading, severity, progression, and age at diagnosis
Color fundus photographs were graded for DR severity in a masked fashion by the Wisconsin Fundus Photograph Reading Center in Madison. The modified Early Treatment of Diabetic Retinopathy Study Airlie House classification of DR was used.23,24 Level 10 indicates no DR; levels 20 to 53, nonproliferative DR of increasing severity; and levels 61 to 85, PDR of increasing severity.24
The following variables were recorded and defined:
Severe DR is defined as an Early Treatment of Diabetic Retinopathy Study level of 53 or greater in the worse eye or history of panretinal laser photocoagulation or vitrectomy for PDR.24 For patients with severe DR, age and duration of DM are recorded at the time that severe DR was first documented, ie, either at the time of the first laser or vitrectomy procedure, as recorded in the patients' medical record, or if no procedure had been done at the time of the study examination when severe DR was found. For patients without severe DR, clinical characteristics are those recorded at the time of the last follow-up examination.
Progression of DR was defined in the 337 patients in the New Jersey 725 study who had nonproliferative DR at baseline (ie, DR severity level in the worse eye of <61 and no panretinal laser photocoagulation or vitrectomy). For those patients, progression at the 6-year follow-up was considered absent if DR severity level in the worse eye remained below 61 and there was either (1) no change in DR severity level (eg, severity level of 35 at both baseline and 6-year follow-up) or (2) an increase of 2 or fewer severity levels (eg, level 10 at baseline increasing to level 35 at 6-year follow-up). Progression was considered severe if DR severity level at the 6-year follow-up either (1) increased to 61 or higher and/or the patient had undergone panretinal laser photocoagulation or vitrectomy, or (2) went from level 10 at baseline to level 53 at the 6-year follow-up. All other patients were considered to have intermediate progression.
Age at diagnosis of DM was defined as the age at which the diagnosis of DM was first recorded in the patient's hospital record by a physician. Systemic hypertension was defined as present if either the systolic blood pressure was 140 mm Hg or higher and/or the diastolic blood pressure was 90 mm Hg or higher, or if the patient was taking antihypertensive medication. Microproteinuria was considered to be present if the albumin excretion rate was 20 to 200 μg/minute. Overt proteinuria was considered to be present if the baseline albumin excretion rate was greater than 200 μg/minute or the patient had dialysis or had had a kidney transplant.
Selection of Candidate Genes and Single-Nucleotide Polymorphisms
Single-nucleotide polymorphisms (SNPs) were chosen primarily from among genes that appear to be good candidates for either involvement in the metabolic processes underlying the events leading to DR or the clinical risk factors for DR as well as from those that have previously demonstrated potential associations with DR.13,15,16 Special attention was given to genes involved in glucose transport and metabolism, angiogenesis, inflammation, neurotransmission, hypertension, and retinal development. A total of 1536 SNPs were selected to construct a GoldenGate Custom Panel (Illumina Inc, San Diego, California). Once a gene was selected, on average 8 SNPs were chosen based on their distribution across the primary block structures of the gene to capture the haplotype diversity across the gene. A set of tagging SNPs was first selected using Tagger.28 These were then assessed for the availability of a GoldenGate assay (Illumina). Preference was given to nonsynonymous SNPs and those reported to have minor allele frequencies greater than 0.10 in more than 1 population. The 5′ (1000 base pairs) and 3′ (2500 base pairs) noncoding regions were included as part of the definition of a gene for SNP selection. Plates were constructed with duplicate and quality-control samples. Genotyping was performed at the University of Texas Southwestern Medical Center's Microarray Core Facility, Dallas.
Assessment of Population Stratification Using Ancestry Informative Markers
The samples have been previously genotyped for 186 ancestry markers.29 The same ancestry informative markers have also been genotyped in 1051 individuals from the 51 worldwide populations represented in the Human Genome Diversity Project–Centre d’Etude du Polymorphisme Humain Human Genome Diversity Cell Line Panel (http://www.cephb.fr/HGDP-CEPH-Panel). The program structure 2.2 (http://pritch.bsd.uchicago.edu/software.html) has been run simultaneously using the ancestry informative marker genotypes from our sample and the 51 Centre d'Etude du Polymorphisme Humain populations to identify population substructure and to compute individual ethnic factor scores. This ancestry assessment showed a lack of substantial substructure with a European factor score on average of 0.09 (median, 0.04). Both a Middle East and an Asian factor had an average score of 0.06 (median, 0.04).
All SNPs were assessed for quality control, which included testing for Hardy-Weinberg equilibrium, call rate, and minor allele frequencies. Two strategies were used in the analysis. For individual SNPs, analyses were performed irrespective of quality-control considerations, but significant SNPs that failed quality-control tests were eliminated. For haplotype analyses, SNPs were removed prior to analysis based on a minor allele frequency of less than 0.05, a call rate of less than 0.80, or P < .001 for departure from Hardy-Weinberg equilibrium.
Testing of individual SNPs was done using logistic regression with sex, diabetes duration, glycohemoglobin, and cholesterol as covariates. Haplotype trend regression for 2- to 6-locus haplotypes, using sliding windows, was also performed, with the same covariates as with individual SNPs.30 Analyses were conducted using HelixTree (Golden Helix Inc, Bozeman, Montana).
Clinical characteristics of the patients with (n = 128) and without (n = 309) severe DR are presented in Table 1. Compared with patients without severe DR, those with severe DR were more likely to have a longer duration of DM (P = .003), systemic hypertension (P < .001), overt proteinuria (P < .001), higher blood cholesterol levels (P < .001), and depression (P < .001); and to be older (P < .001). There was no significant difference in mean follow-up between patients in the New Jersey 725 study with (n = 124) and without (n = 295) severe DR (mean [standard deviation (SD)], 7.6 [2.1] years vs 7.3 [2.0] years; t417 = 1.26, P = .2).
A total of 1536 SNPs from 193 retinopathy candidate genes were selected. An overall call rate of 98% was obtained. Of the 1536 SNPs, 10 in this sample were monomorphic and were excluded. Following adjustment for sex, duration of DM, glycosylated hemoglobin, and cholesterol, 5 of the 1526 were significant at P < .001, 12 were significant at P < .01 but P > .001, and 61 were significant at P < .05 but P > .01. Of these, 3, 11, and 52 SNPs, respectively, also met all quality-control criteria. Significant associations between SNPs and severe DR are presented in Table 2 for the genes with at least 1 SNP at P < .01. Only the most significant SNP for each gene is tabulated after adjustment. Results for all genes and SNPs under different adjustments and their quality-control characteristics are provided in a supplemental table (http://www.umdnj.edu/eyeweb/library/supplemental_table.pdf). These results were largely robust to adjustment for other clinical risk factors for DR (ie, hypertension, proteinuria, or depression).
To get a handle on the contribution of variation in each of these candidate genes to retinopathy susceptibility (as opposed to the contribution of individual SNPs), we used a sliding-window haplotypes approach using windows that ranged from 2 to 6 SNPs and we used a graphical representation of an assessment of P values to examine results (GrASP31). Haplotype analysis led to the classification of 4 genes as being of particular interest: BBS2, HTR1B, a region containing both PROS1 and ARL6, and DRD2. We illustrate the approach based on BBS2 (Figure). Fifteen SNPs were genotyped in BBS2. The flanking SNPs were rs2288056 and rs17841923. In the single SNP analysis, 2 SNPs demonstrated significance at P = .01: rs4784675 (Table 2) and rs12596017. Haplotype analysis identified a region of BBS2 in which haplotypes consistently demonstrated a strong association with DR, seemingly centered on rs4784675 with P = 1.34 × 10−4 (Figure). Similar results were obtained for the other 3 genes/regions. In each instance for these 4 candidates, at least 1 of the haplotype analyses among the set of all haplotype analyses for that gene exceeded a Bonferroni-corrected P value of .05.
While a comparable set of data is not available for replication, we analyzed the longitudinal data for progression of DR. In this analysis, those with the most severe DR were excluded, as there was no further progression to be documented. Individuals were classified as having little or no change vs progressors (either intermediate or progression to severe disease). In this analysis, 95 SNPs were significant (P = .05) with 76 meeting all quality-control criteria. This includes 4 (3 passing quality control) that were significant at P < .001 and 19 (14 passing quality control) at P = .01. Table 3 lists the most significant SNP in each of the genes that have at least 1 SNP at P < .01. Note that SLC2A1, FLT1, and HLA-B have the highest significance for both prevalent disease as well as for progression and that the same SNP for both is most associated. While HTR1B, BBS2, ROBO2, DRD2, and ANGPT1 have the highest significance for prevalent disease and do not appear in Table 3 with P < .01, they each have at least 1 SNP that is significant at P = .05 for progression.
In the present study, we found that SNPs in 10 genes involved in glucose transport and metabolism, angiogenesis, neurotransmission, hypertension, and retinal development were significantly associated with severity of DR in African Americans with type 1 DM. Three of those same genes were also significantly associated with the progression of DR. These data confirm a role of genetic factors in relation to the development of DR and indicate that more than 1 pathway may be involved.12,14 These results were robust to adjustment for other clinical risk factors for DR in this population. We will not discuss each gene that demonstrated association. Rather, we will highlight the biological plausibility for several to illustrate the merits and implications of these results.
On chromosome 1, 1 of the glucose transporter genes (SLC2A1 or GLUT1)—a member of a family of sodium-independent glucose transporter proteins—is significantly associated with both severe DR and progression of DR. GLUT1 is the predominant glucose transporter across endothelial cells of the inner blood-retinal barrier into the retina.32,33 In DM, increased glucose transport and/or GLUT1 expression in endothelial cells is upregulated by hypoxia, growth factors, and/or cytokines, all of which are present in DR.34-36GLUT1 is also expressed in the retina in nonvascular cells (ie, glia, ganglion cells, and photoreceptors).33 In DM, those cells show abnormalities that may contribute to the vascular changes of DR.37 Because hyperglycemia is 1 of the strongest clinical risk factors for progression of DR, GLUT1 is a likely candidate gene for DR.38 It is noteworthy that polymorphism of GLUT1 has so far been implicated only in diabetic nephropathy.16,39,40 Oxidative stress resulting from hyperglycemia is another potential etiopathogenic factor for DR.13,15 In support of this is our finding that genes with antioxidant properties, RXRA and CAT, are significantly associated with progression of DR.41-43
Neovascularization and increased retinal vascular permeability are present in DR and are the 2 major causes of visual loss.3 In our African American patients with diabetes, 2 genes related to angiogenesis—ANGPT1 on chromosome 8 and FLT1 on chromosome 13—are significantly associated with severe DR and/or its progression. Angiopoietin 1 is a protein secreted by a variety of cells, including pericytes. It has angiogenic actions that are distinct from those of vascular endothelial growth factor and are mediated via a tyrosine kinase receptor expressed almost exclusively on endothelial cells.44,45 Angiopoietin 1 also has anti-inflammatory properties, suppressing the expression of adhesion molecules and blocking vascular permeability through vascular endothelial growth factor inhibition and strengthening of endothelial tight junctions.46FLT1 is a tyrosine kinase receptor, which is expressed on the surface of retinal vascular endothelial cells and mediates the biological effects of vascular endothelial growth factor.47,48FLT1 is also expressed in peripheral blood monocytes and neutrophils, where it triggers chemotactic migration.49 Thus, both ANGPT1 and FLT1 have a key role not only in angiogenesis and modulation of vascular permeability, but also in inflammation. Clinical and experimental data support the role of inflammation in DR.50 In the present study, other genes involved either in inflammation (PLA2G4A, OLR1, and PPARG) or in the immune response (HLA-B) are associated with progression of DR, further underlining the close relationship of angiogenic and inflammatory pathways in DR. It is noteworthy, however, that while HLA polymorphisms have been implicated in the susceptibility to type 1 DM, previously published studies investigating their possible role in the development of DR have yielded conflicting results.51
The ENPP1 gene on chromosome 6 is a type II transmembrane glycoprotein that cleaves various substrates, eg, the phosphodiester bonds of nucleotide sugars.52ENPP1 is thought to inhibit insulin signal transduction by interacting with the insulin receptor α subunit.52 Overexpression of ENPP1 results in insulin resistance, a metabolic abnormality that is present in type 1 DM and that has been linked to the vascular complications of DM.52,53ENPP1 is also a binding partner of integrins—extracellular matrix proteins involved in cell adhesion, cell communication, and angiogenesis.52,54 In our African American patients, the integrin β5 gene is associated with progression of DR. Interestingly, the integrin β5 protein is expressed in the retinal fibrovascular tissue of PDR.55,56
In the present study, dopamine receptors DRD1 and DRD2 (located on chromosomes 5 and 11, respectively) and the serotonin receptor HTR1B (located on chromosome 6) show an association with severe DR and/or its progression, though DRD1 had a minor allele frequency of less than 0.05. DRD1 and DRD2 are expressed in the retina, where dopamine is the main catecholamine.32,57 Dopamine, in addition to its effects as a neurotransmitter, modulates retinal vessel diameter and retinal blood flow.58 The DRD1 receptor gene is also involved in blood pressure regulation, and polymorphisms in this gene have been implicated in essential hypertension.59,60HTR1B is expressed in ganglion cells in the retina.61 In addition to being a neurotransmitter, serotonin is a major product of platelet activation and induces endothelium-dependent vasodilation through the formation of nitric oxide.61 Thus, DRD1, DRD2, and HTR1B could influence the development of DR either through signaling within retinal cells or by influencing retinal blood flow. Furthermore, growth factors, eg, vascular endothelial growth factor, appear to affect both vascular and nervous systems, and this may have potential relevance to DR.62
Our data also indicate that genes involved in retinal development are associated with severe DR. In fact, of all the genes reported here, BBS2 shows the strongest association with severe DR (Figure). Little is known about the functions of the Bardet-Biedl syndrome proteins except that BBS2 abnormalities have been linked to retinal degeneration and increased incidence of DM and hypertension.63ROBO2 is an axon-guidance receptor located in the cell membrane. It belongs to the immunoglobulin superfamily and is expressed in the retina.32,64,65ROBO2 is also involved in cell adhesion and chemotaxis, both of which may explain its potential role in DR. The role of these developmental genes in relation to DR, however, remains to be elucidated.
Strengths of our study include the geographically well-defined diabetic African American population, for whom cross-sectional and longitudinal DR data as well as clinical risk factors for DR are available, and in whom single-gene as well as haplotype associations were examined. While only some of the candidate genes and specifically chosen SNPs were included, the data gathered thus far are unique and provide support for some of the proposed mechanisms underlying the development of DR.
Because the pathogenesis of DR likely involves numerous pathways, some contributory genes may have been omitted. Future genome-wide association studies are expected to yield information for identifying additional genes of importance in the development of DR. Our findings may be confounded by the use of multiple comparisons, though we have been careful to use conservative P values. Finally, results of the study may not apply to other populations because of racial differences in genetic risks for the disease. This does not mean, however, that genes implicated herein cannot affect susceptibility in other populations. A challenge with the present study is the lack of comparable data for replication. The longitudinal data collected become valuable in this regard, as one would expect that some genes contributing to the development of disease would also contribute to the progression of disease. Thus, those genes implicated in both Tables 2 and 3 would be given higher priority for follow-up.
To date, efforts to reduce severity of DR have targeted clinical risk factors for the disease, aiming specifically at tight glycemic and blood pressure control. These changes are often either not attained or only partially achieved. Identifying genes that may be responsible for severity of the disease may help not only to better understand the pathogenesis but also to develop new approaches to the treatment of DR. The data we reported herein provide support for a polygenic component of severe DR. Additional studies that examine other candidate genes for the development of DR in our population of African Americans with type 1 DM are ongoing.
Correspondence: Monique S. Roy, MD, The Institute of Ophthalmology and Visual Science, University of Medicine and Dentistry of New Jersey, New Jersey Medical School, 90 Bergen St, Ste 6164, Newark, NJ 07101-1709 (roymo@umdnj.edu).
Submitted for Publication: September 8, 2008; final revision received December 19, 2008; accepted January 5, 2009.
Author Contributions: Dr Roy had full access to all of the data in the study and takes full responsibility for the integrity of the data and the accuracy of the data analysis.
Financial Disclosure: None reported.
Funding/Support: This research was supported by grant 8-2004-780 from the Juvenile Diabetes Research Foundation and by a Lew Wasserman Merit Award from Research to Prevent Blindness.
1.National Society to Prevent Blindness, Vision Problems in the US: Data Analysis, Definitions, Data Sources, Detailed Data Tables, Analysis, Interpretation. New York, NY National Society to Prevent Blindness1980;
3.Klein
RKlein
B Vision disorders in diabetes. National Diabetes Data Group,
Diabetes in America. 2nd ed. Bethesda, MD National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases1995;293- 338
NIH publication 95-1468 Google Scholar 4.Roy
MS Diabetic retinopathy in African-Americans with type 1diabetes: The New Jersey 725, II: risk factors.
Arch Ophthalmol 2000;118
(1)
105- 115
PubMedGoogle ScholarCrossref 5.Roy
MSRoy
AAffouf
M Depression is a risk factor for poor glycemic control and retinopathy in African-Americans with type 1 diabetes.
Psychosom Med 2007;69
(6)
537- 542
PubMedGoogle ScholarCrossref 7.Diabetes Control and Complications Trial Research Group, Clustering of long-term complications in families with diabetes in the Diabetes Control and Complications Trial.
Diabetes 1997;46
(11)
1829- 1839
PubMedGoogle ScholarCrossref 8.Rema
MSaravanan
GDeepa
RMohan
V Familial clustering of diabetic retinopathy in South Indian type 2 diabetic patients.
Diabet Med 2002;19
(11)
910- 916
PubMedGoogle ScholarCrossref 9.Hallman
DMHuber
JC
JrGonzalez
VKlein
BKlein
RHanis
C Familial aggregation of severity of diabetic retinopathy in Mexican Americans from Starr County, Texas.
Diabetes Care 2005;28
(5)
1163- 1168
PubMedGoogle ScholarCrossref 10.Monti
MCLonsdale
JMontomoli
CMontross
RSchlag
EGreenberg
D Familial risk factors for microvascular complications and differential male-female risk in a large cohort of American families with type 1 diabetes.
J Clin Endocrinol Metab 2007;92
(12)
4650- 4655
PubMedGoogle ScholarCrossref 11.Looker
HCNelson
RChew
E
et al. Genome-wide linkage analyses to identify loci for diabetic retinopathy.
Diabetes 2007;56
(4)
1160- 1166
PubMedGoogle ScholarCrossref 14.Uhlmann
KKovacs
PBoettcher
YHammes
H-PPaschke
R Genetics of diabetic retinopathy.
Exp Clin Endocrinol Diabetes 2006;114
(6)
275- 294
PubMedGoogle ScholarCrossref 17.Al-Kateb
HMirea
LXie
X
et al. Multiple variants in vascular endothelial growth factor (VEGFA) are risk factors for time to severe retinopathy in type 1 diabetes: The DCCT/EDIC Genetics study.
N Engl J Med 2005;3532643- 2653
PubMedGoogle ScholarCrossref 18.Hallman
DMBoerwinkle
EGonzalez
VKlein
BKlein
RHanis
C A genome-wide linkage scan for diabetic retinopathy susceptibility genes in Mexican Americans with type 2 diabetes from Starr County, Texas.
Diabetes 2007;56
(4)
1167- 1173
PubMedGoogle ScholarCrossref 19.Churchill
AJCarter
JRamsden
C
et al. VEGF polymorphisms are associated with severity of diabetic retinopathy.
Invest Ophthalmol Vis Sci 2008;49
(8)
3611- 3616
PubMedGoogle ScholarCrossref 20.Roy
MS Diabetic retinopathy in African-Americans with type 1 diabetes: The New Jersey 725, I: methodology, population, frequency of retinopathy and visual impairment.
Arch Ophthalmol 2000;118
(1)
97- 104
PubMedGoogle ScholarCrossref 21.Roy
MSAffouf
M Six-year progression of retinopathy and associated risk factors in African American patients with type 1 diabetes mellitus: the New Jersey 725.
Arch Ophthalmol 2006;124
(9)
1297- 1306
PubMedGoogle ScholarCrossref 22.The Diabetic Retinopathy Study Research Group, A modification of the Airlie House classification of diabetic retinopathy: Diabetic Retinopathy Study report number 7.
Invest Ophthalmol Vis Sci 1981;21210- 226
Google Scholar 23.Early Treatment of Diabetic Retinopathy Study Research Group, Grading diabetic retinopathy from stereoscopic color fundus photographs: an extension of the modified Airlie House classification. ETDRS report number 10.
Ophthalmology 1991;98
(5)
((suppl))
786- 806
PubMedGoogle ScholarCrossref 24.Early Treatment of Diabetic Retinopathy Study Research Group (ETDRS), Fundus photographic risk factors for progression of diabetic retinopathy. ETDRS report number 12.
Ophthalmology 1991;98
(5)
((suppl))
823- 833
PubMedGoogle ScholarCrossref 25.Council on Clinical Classifications, International Classification of Diseases, Ninth Revision, Clinical Modification. 1 Ann Arbor, MI Edwards Brothers Inc1978;
26. Report of the Expert Committee on the diagnosis and classification of diabetes mellitus.
Diabetes Care 1997;20
(7)
1183- 1197
PubMedGoogle Scholar 27.Winter
WEMacLaren
NRiley
WClarke
DKappy
MSpillar
R Maturity-onset diabetes of youth in black Americans.
N Engl J Med 1987;316
(6)
285- 291
PubMedGoogle ScholarCrossref 28.de Bakker
PIWYelensky
RPe’er
IGabriel
SBDaly
MJAltshuler
D Efficiency and power in genetic association studies.
Nat Genet 2005;37
(11)
1217- 1223
PubMedGoogle ScholarCrossref 29.Hodgkinson
CAYuan
QXu
K
et al. Addictions biology: haplotype-based analysis for 130 candidate genes on a single array.
Alcohol Alcohol 2008;43
(5)
505- 515
PubMedGoogle ScholarCrossref 30.Zaykin
DVWestfall
PHYoung
SSKarnoub
MAWagner
MHEhm
MG Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals.
Hum Hered 2002;53
(2)
79- 91
PubMedGoogle ScholarCrossref 31.Mathias
RAGao
PGoldstein
JL
et al. A graphical assessment of p-values from sliding window haplotype tests of association to identify asthma susceptibility loci on chromosome 11q.
BMC Genet 2006;738
PubMedGoogle ScholarCrossref 32.Diehn
JJDiehn
MMarmor
MBrown
P Differential gene expression in anatomical compartments of the human eye.
Genome Biol 2005;6
(9)
R74
PubMedGoogle ScholarCrossref 33.Kumagai
AKGlasgow
BPardridge
W GLUT1 glucose transporter expression in the diabetic and nondiabetic human eye.
Invest Ophthalmol Vis Sci 1994;35
(6)
2887- 2894
PubMedGoogle Scholar 34.Takagi
HKing
GAiello
L Hypoxia upregulates glucose transport activity through adenosine-mediated increase of GLUT1 expression in retinal capillary endothelial cells.
Diabetes 1998;47
(9)
1480- 1488
PubMedGoogle ScholarCrossref 35.Sone
HDeo
BKumagai
A Enhancement of glucose transport by vascular endothelial growth factor in retinal endothelial cells.
Invest Ophthalmol Vis Sci 2000;41
(7)
1876- 1884
PubMedGoogle Scholar 36.Fernandes
RSuzuki
KKumagai
A Inner blood-retinal barrier GLUT1 in long-term diabetic rats: an immunogold electron microscopic study.
Invest Ophthalmol Vis Sci 2003;44
(7)
3150- 3154
PubMedGoogle ScholarCrossref 37.Gardner
TWAntonetti
DBarber
ALaNoue
KFLevison
SW Diabetic retinopathy: more than meets the eye.
Surv Ophthalmol 2002;47
((suppl 2))
S253- S262
PubMedGoogle ScholarCrossref 38.The Diabetes Control and Complications Trial Research Group, The effect of intensive diabetes treatment on the progression of diabetic retinopathy in insulin-dependent diabetes mellitus.
Arch Ophthalmol 1995;113
(1)
36- 51
PubMedGoogle ScholarCrossref 39.Tarnow
LGrarup
NHansen
TParving
H-HPedersen
O Diabetic microvascular complications are not associated with two polymorphisms in the GLUT-1 and PC-1 genes regulating glucose metabolism in Caucasian type 1 diabetic patients.
Nephrol Dial Transplant 2001;16
(8)
1653- 1656
PubMedGoogle ScholarCrossref 40.Hodgkinson
ADPage
TMillward
BDemaine
A A novel polymorphism in the 5′ flanking region of the glucose transporter (GLUT1) gene is strongly associated with diabetic nephropathy in patients with type 1 diabetes mellitus.
J Diabetes Complications 2005;19
(2)
65- 69
PubMedGoogle ScholarCrossref 41.Nayak
MSKita
MMarmor
M Protection of rabbit retina from ischemic injury by superoxide dismutase and catalase.
Invest Ophthalmol Vis Sci 1993;34
(6)
2018- 2022
PubMedGoogle Scholar 42.Chai
DWang
BShen
LPu
JZhang
XHe
B RXR agonists inhibit high-glucose induced oxidative stress by repressing PKC activity in human endothelial cells.
Free Radic Biol Med 2008;44
(7)
1334- 1347
PubMedGoogle ScholarCrossref 43.Flekac
MSkrha
JHilgertova
JLacinova
ZJarolimkova
M Gene polymorphisms of superoxide dismutases and catalase in diabetes mellitus.
BMC Med Genet 2008;930
PubMedGoogle ScholarCrossref 44.Papapetropoulos
AGarcia-Cardeña
GDengler
TMaisonpierre
PCYancopoulos
GDSessa
WC Direct actions of angiopoietin-1 on human endothelium: evidence for network stabilization, cell survival, and interaction with other angiogenic growth factors.
Lab Invest 1999;79
(2)
213- 223
PubMedGoogle Scholar 45.Wang
YLHui
YGuo
BMa
J Strengthening tight junctions of retinal microvascular endothelial cells by pericytes under normoxia and hypoxia involving angiopoietin-1 signal way.
Eye 2007;21
(12)
1501- 1510
PubMedGoogle ScholarCrossref 47.Kim
IRyan
ARohan
R
et al. Constitutive expression of VEGF, VEGFR-1, and VEGFR-2 in normal eyes.
Invest Ophthalmol Vis Sci 1999;40
(9)
2115- 2121
PubMedGoogle Scholar 48.Caldwell
RBBartoli
MBehzadian
A
et al. Vascular endothelial growth factor and diabetic retinopathy: role of oxidative stress.
Curr Drug Targets 2005;6
(4)
511- 524
PubMedGoogle ScholarCrossref 49.Usui
TIshida
SYamashiro
K
et al. VEGF164(165)as the pathological form: differential leukocyte and endothelial responses through VEGFR1 and VEGFR2.
Invest Ophthalmol Vis Sci 2004;45
(2)
368- 374
PubMedGoogle ScholarCrossref 50.Joussen
AMPoulaki
VLy Le
M
et al. A central role for inflammation in the pathogenesis of diabetic retinopathy.
FASEB J 2004;18
(12)
1450- 1452
PubMedGoogle Scholar 51.Wong
TYCruickshanks
KKlein
R
et al. HLA-DR3 and DR4 and their relation to the incidence and progression of diabetic retinopathy.
Ophthalmology 2002;109
(2)
275- 281
PubMedGoogle ScholarCrossref 52.Bollen
MGijsbers
RCeulemans
HStalmans
WStefan
C Nucleotide pyrophosphatases/phosphodiesterases on the move.
Crit Rev Biochem Mol Biol 2000;35
(6)
393- 432
PubMedGoogle ScholarCrossref 53.DeFronzo
RAHendler
RSimonson
D Insulin resistance is a prominent feature in insulin-dependent diabetes.
Diabetes 1982;31
(9)
795- 801
PubMedGoogle ScholarCrossref 55.Roth
TPodesta
FStepp
MABoeri
DLorenzi
M Integrin overexpression induced by high glucose and by human diabetes: potential pathway to cell dysfunction in diabetic microangiopathy.
Proc Natl Acad Sci U S A 1993;90
(20)
9640- 9644
PubMedGoogle ScholarCrossref 56.Friedlander
MTheesfeld
CSugita
M
et al. Involvement of integrins alpha v beta 3 and alpha v beta 5 in ocular neovascular diseases.
Proc Natl Acad Sci U S A 1996;93
(18)
9764- 9769
PubMedGoogle ScholarCrossref 57.Missale
CNash
RRobinson
SWJaber
MCaron
MG Dopamine receptors: from structure to function.
Physiol Rev 1998;78
(1)
189- 225
PubMedGoogle Scholar 58.Huemer
K-HGarhöfer
GZawinka
C
et al. Effects of dopamine on human retinal vessel diameter and its modulation during flicker stimulation.
Am J Physiol Heart Circ Physiol 2003;284
(1)
H358- H363
PubMedGoogle Scholar 59.Sato
MSoma
MNakayama
TKanmatsuse
K Dopamine D1 receptor gene polymorphism is associated with essential hypertension.
Hypertension 2000;36
(2)
183- 186
PubMedGoogle ScholarCrossref 60.Beige
JBellmann
ASharma
AGessner
R Ethnic origin determines the impact of genetic variants in dopamine receptor gene (DRD1) concerning essential hypertension.
Am J Hypertens 2004;17
(12, pt 1)
1184- 1187
PubMedGoogle ScholarCrossref 61.Yakel
J The 5-HT3 receptor channel: function, activation and regulation. Endo
MKurachi
YMishina
M
Pharmacology of Ionic Channel Function–Activators and Inhibitors: Handbook of Experimental Pharmacology. Berlin, Germany Springer-Verlag2000;147541- 560
Google Scholar 62.Raab
SPlate
K Different networks, common growth factors: shared growth factors and receptors of the vascular and the nervous system.
Acta Neuropathol 2007;113
(6)
607- 626
PubMedGoogle ScholarCrossref 63.Nishimura
DYFath
MMullins
R
et al. Bbs-2 null mice have neurosensory deficits, a defect in social dominance, and retinopathy associated with mislocalization of rhodopsin.
Proc Natl Acad Sci U S A 2004;101
(47)
16588- 16593
PubMedGoogle ScholarCrossref 64.Yue
YGrossmann
BGaletzka
DZechner
UHaaf
T Isolation and differential expression of two isoforms of the ROBO2/Robo2 axon guidance receptor gene in humans and mice [published online ahead of print July 10, 2006].
Genomics 2006;88
(6)
772- 778
PubMedGoogle ScholarCrossref