Plasminogen activator inhibitor-1 4G/5G polymorphism and retinopathy risk in type 2 diabetes: a meta-analysis

Diabetic retinopathy (DR), the leading cause of blindness in the working population, is associated with a strong genetic predisposition, highlighted by the familial clustering of DR [1, 2]. Several gene polymorphisms are associated with DR, such as in the methylenetetrahydrofolate reductase gene, endothelial nitric oxide synthase gene, manganese superoxide dismutase gene, vascular endothelial growth factor gene, receptor for advanced glycation end products gene, aldose reductase 2 gene and P-selectin gene, among others [3‐9]. Plasminogen activator inhibitor-1 (PAI-1), the most important in vivo inhibitor of plasminogen activation, has also been implicated in DR. In addition to being involved in tissue repair and remodeling, PAI-1 plays a critical role in the regulation of intravascular fibrinolysis. In patients with type 2 diabetes (T2D), impaired fibrinolysis is involved in the pathogenesis of DR [10]. Increased PAI-1 expression has been associated with matrix accumulation [11] and the development of basement membrane thickening and pericyte loss, which are regarded as the earliest retinal pathohistological changes in DR in transgenic mice [10, 12]. PAI-1 activity, which is affected by PAI-1 gene polymorphisms and metabolic determinants, is also elevated in DR [13]. Compared with other PAI-1 variants, the most significant variation in PAI-1 expression resides in a common single-base-pair guanine insertion/deletion polymorphism (4G/5G) within the promoter region of the PAI-1 gene at nucleotide position -675 [11, 14]. Unlike the 5G allele that binds a transcription repressor protein, resulting in low PAI-1 expression, the 4G allele does not bind a transcription repressor, thus conferring a 'high PAI-1 expressor' nature to the allele [15].

Considering the potential influence on the individual risk for DR due to the insertion-deletion mutation of -675 4G/5G, many studies have explored the association between PAI-1 4G/5G and DR risk [16‐24]. However, individual studies yielded inconsistent and even conflicting findings, which might be caused by the limitation of individual studies. To shed light on these contradictory results and to get a more precise evaluation of this association, we performed a meta-analysis of nine published case-control studies covering 1, 217 cases and 1, 459 controls.

Unraveling the genes that contribute to the pathogenic risk of DR has been one of the major foci of basic research in DR over the past few decades. A large number of putative genes and genetic variants have been reported to be associated with higher risk of DR. A genome-wide association study performed on Mexican-Americans found several SNPs and genes associated with severe DR. None of these loci have been previously linked to DR or diabetes itself [31]. Another genome-wide association study on Taiwanese populations identified five loci not previously associated with DR susceptibility in T2D [32]. This suggests that, until now, no genes have achieved widespread acceptance as conferring high risk of DR in patients with T2D [33]. After a review of the meta-analyses of DR-related gene polymorphisms, only the C677T polymorphism in the methylenetetrahydrofolate reductase gene was detected to moderately augment the risk of DR in T2D overall [34, 35]. The Gly82Ser polymorphism in the receptor for advanced glycation end products gene might be considered a risk factor for DR in Asian populations. Moderate evidence was founded for a correlation between the angiotensin-converting enzyme gene and proliferative DR [36]. However, neither the angiotensin-converting enzyme gene insertion/deletion [36‐38] nor the vascular endothelial growth factor -634C/G gene [39] showed a significant relationship with DR, either overall or in ethnicity subgroups in meta-analysis so far.

The earliest investigation into PAI-1 polymorphism and DR risk, reported by Nagi et al., revealed a positive relationship between the 4G allele of PAI-1 [19] and DR risk in Pima Indians, whose incidence of diabetes, particularly non-insulin-dependent diabetes, was extremely high [40, 41]. However, in the subsequent studies in Caucasian populations, a trend of studies with a lack of association was suggested [16, 18, 20, 21]. But in a recent larger case-control study in Tunisia that contained a total of 856 adult patients with T2D, Ezzidi et al. reported a significantly higher frequency of the 4G/4G genotype (OR 1.64, 95%CI 1.10 to 2.43), indicating 4G/4G in PAI-1 locus as a risk factor for DR [17]. All the studies in East Asian populations showed no relationship between 4G/5G polymorphism and DR risk [22‐24]. Our meta-analysis confirmed that the 4G/4G genotype of the PAI-1 carried more risk in Caucasian but not Asian participants, even though the overall effect was positive. The differences in ethnic backgrounds, lifestyle, nutrition and living environment may partly explain this discrepancy [42]. We also found a marginally significant susceptibility to DR of T2D between PAI-1 4G/5G polymorphism to the population with longer duration of T2D. This subgroup analysis manifested a gene-environment interaction and highlighted the need for implementing rigorous case-selective criterion in future studies.

We also observed inconsistent results between hospital-based studies and population-based studies, which may be explained by the biases in hospital-based studies. Control cases in hospital-based studies may be less representative of the general population than those from population-based studies. Genes do not work in isolation; instead, complex molecular networks and cellular pathways are often involved in disease susceptibility [43]. Taking into account that DR is a complex disease with multifactorial, polygenic and environmental influences, a minor contributing pathogenic role of the PAI-1 polymorphism in specific cases in DR and in co-operation with other factors cannot be totally excluded.

Several potential limitations existed in our meta-analysis and our results should be interpreted with caution. First, as no correction for multiple testing was performed in this meta-analysis, false positive results may have been induced in some fraction because of the application of multiple statistical tests, which would increase the probability of type I errors. Second, our meta-analysis is based on unadjusted estimates because of a lack of original data. For example, the accurate disease time-course of individual patients was unavailable, which may potentially have affected the results where our classification criterion was according to the mean value of the diabetes duration. Third, this meta-analysis was limited by the small sample size - especially in subgroup analysis - though the Egger's test gave no publication bias [44]. Fourth, the existing studies lacked information about potential gene-gene interactions. Last, genotyping methods were different among selected studies, which might affect results. This discrepancy indicates the need to implement rigorous quality control procedures in future studies.