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Review

No Association of Angiotensin-Converting Enzyme Insertion/Deletion (ACE I/D) Gene Polymorphism in the Susceptibility to Diabetic Retinopathy in Type 2 Diabetes Mellitus Patients: An Updated Meta-Analysis

by
Aline Ruilowa de Pinho Coelho
1,
Luciana Carvalho Silveira
1,
Kamilla de Faria Santos
1,
Rodrigo da Silva Santos
1,2,* and
Angela Adamski da Silva Reis
1,2,*
1
Laboratory of Molecular Pathology, Biological Sciences Institute, Federal University of Goiás, Goiânia 74690-090, Brazil
2
Department of Biochemistry and Molecular Biology, Biological Sciences Institute, Federal University of Goiás, Goiânia 74690-090, Brazil
*
Authors to whom correspondence should be addressed.
J. Pers. Med. 2023, 13(9), 1308; https://doi.org/10.3390/jpm13091308
Submission received: 10 July 2023 / Revised: 10 August 2023 / Accepted: 17 August 2023 / Published: 26 August 2023
(This article belongs to the Special Issue Biomarkers for Inflammatory and Metabolic Disorders)
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Abstract

:
Diabetic retinopathy (DR) is a complex and multifactorial pathology encompassing environmental, metabolic, and polygenic influences. Among the genes possibly involved in the development and progression of DR, the Angiotensin I-converting enzyme (ACE) gene stands out, which presents an insertion (I) or deletion (D) polymorphism of a 287 bp Alu repetitive sequence in intron 16. Thus, this study aimed to perform a systematic review with meta-analysis to elucidate the relationship between the ACE gene (I/D) polymorphism (rs1799752) and the development and progression of DR in type 2 diabetic patients. PubMed/MEDLINE, Embase, Web of Science, and Scopus databases were systematically searched to retrieve articles that investigated the association between ACE gene (I/D) polymorphism in DR patients. Sixteen articles were included in the systematic review. The results describe no significant association between the polymorphism and DR risk (OR = 1.12; CI = 0.96–1.31; and p = 0.1359) for genotypic analysis by the dominant model (II vs. ID+DD). Moreover, we also observed no significant association between the D allele on the allele frequency analysis (I vs. D) and the DR risk (OR = 1.10; CI = 0.98–1.23; and p = 0.1182). Forest plot analysis revealed that the discrepancy between previous studies most likely arose from variations in their sample sizes. In conclusion, I/D polymorphism appears to be not involved in the susceptibility to and progression of the DR in type 2 diabetic patients.

1. Introduction

Diabetic retinopathy (DR) is a common microvascular complication of diabetes mellitus (DM), classified as one of the most recurrent causes of blindness and visual impairmentworldwide. However, its etiology has not been fully elucidated [1]. Furthermore, DR is usually asymptomatic in the early stages, highlighting the need for regular ophthalmologic exams that confirm the diagnosis and enable the subsequent management of the disease [2]. There are two categories of DR: non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR) [3].
The increased permeability of capillary pericytes and vascular endothelial damage determine the appearance of microaneurysms and dot intraretinal hemorrhages, which are the main characteristics of NPDR. With disease progression, vasoconstriction and capillary occlusions form tortuous capillaries and retinal ischemia, as well as cotton wool spots that can also be observed at this stage. In the final stage of the disease (PDR), severe hypoxia causes neovascularization, vitreous hemorrhage, and retinal detachment [2,3].
DR is a complex and multifactorial pathology encompassing environmental, metabolic, and polygenic influences. Although the known risk factors are diabetes duration and glycemic control, not all patients with diabetes develop DR. Therefore, genetic variation may explain the heterogeneity in DR progression [4]. Among the genes possibly involved in the development and progression of DR, the Angiotensin I-converting enzyme (ACE) gene stands out, responsible for producing ACE that converts Angiotensin I into Angiotensin II, an important vasoconstrictor that induces the expression of Vascular Endothelial Growth Factor (VEGF), stimulating angiogenesis (increased intraocular angiogenesis that leads to PDR and diabetic macular edema) [5].
The ACE gene is located at 17q23.3 and has 26 exons and 25 introns. More than 160 polymorphisms were identified in this gene [6]. The most studied polymorphism of the ACE gene is characterized by the insertion or deletion (I/D) of a 287 bp Alu repetitive sequence in intron 16 (rs1799752). This polymorphism is associated with increased levels of circulating ACE and a higher activity of this enzyme [7]; the D allele was related to increased ACE activity compared to the presence of the I allele [8,9].
On the other hand, this polymorphism has been implicated in the pathogenesis of DM and its complications. Moreover, this polymorphism has been increasingly highlighted, mainly due to its relationship with the severity of COVID-19 in diabetic patients [10]. Thus, we aimed to perform a systematic review with meta-analysis to elucidate the relationship between the ACE gene (I/D) polymorphism (rs1799752) and the development and progression of DR in type 2 diabetes mellitus (T2DM) patients.

2. Materials and Methods

2.1. Registration and Search Strategy

Based on the guide question “What is the association between the I/D polymorphism of the Angiotensin I Converting Enzyme gene and the development and progression of diabetic retinopathy in patients with type 2 diabetes mellitus?”, a systematic review was conducted to determine the association between the ACE gene (I/D) polymorphism (rs1799752) and DR in T2DM patients. Publications from 1992 to 2022 were selected, comprising the last 30 years of analysis on the subject.
To avoid duplication, this study had the protocol registered in the International Prospective Register of Systematic Reviews (PROSPERO) on 12 December 2020 (number CRD42020215932) (File S1). For a better description of the data, we followed the Preferred Report Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [11].
The literature search occurred between June and December 2022 in the PubMed/MEDLINE, Embase, Web of Science, and Scopus databases. The last access to databases occurred on 13 December 2022. Combined terms for “Polymorphism I/D”, “ACE gene”, and “diabetic retinopathy” were used to elaborate the search strategy, being adapted for each database (Table 1). Filters restricting the last 30 years (1992–2022) were applied to all databases.

2.2. Inclusion and Exclusion Criteria

Inclusion: Observational studies that determined the genotypic distribution of the ACE gene (I/D) polymorphism (rs1799752) in DR patients, in the control (patients with T2DM and without DR) and/or healthy controls; in English; and published from 1992 to 2022.
Exclusion: Studies that did not address the ACE gene (I/D) polymorphism (rs1799752); another study model; and studies with patients with another type of DM.

2.3. Selection of Articles and Evaluation of Methodological Quality

The articles found in the search were included in the Rayyan platform [12]. Two independent reviewers performed the screening in two phases (I and II), in which the articles were evaluated according to predetermined inclusion and exclusion criteria. The first stage was performed by reading the title and abstract, and the second stage consisted of the whole reading of the selected articles in the first stage.
The risk of methodological bias was assessed using the Joanna Briggs Institute (JBI) critical assessment tools for each study design [13]. Only studies that responded positively to at least 70% of the questions were considered low risk of bias. The differences of opinion between the reviewers were discussed and resolved by consensus.

2.4. Data Extraction

Data extraction was performed by two reviewers independently in all studies included, and the following data were extracted: (1) authors and year of publication; (2) country of study; (3) study design; (4) sample size; (5) sexes of sample individuals; (6) average age of the sample; (7) clinical characteristics; and (8) genotypic and allele frequencies. Authors of studies with missing data were contacted.

2.5. Statistical Analysis

A meta-analysis was performed to evaluate the association of the ACE gene (I/D) polymorphism (rs1799752) with DR, using the calculation of the odds ratio (OR) and 95% confidence interval (CI), with the results presented in a forest plot. The ORs were calculated for the comparisons: (i) genotypic comparison with the dominant model (II vs. ID+DD); and (ii) allelic comparison (I vs. D). In addition, the heterogeneity between the studies was evaluated by the Higgins inconsistency test (I2).
The selection of the meta-analytical model was based on the result of the heterogeneity test between the studies. The fixed effect model (Mantel–Haenszel method) was applied when I2 < 25% (low heterogeneity), and the random effect model (DerSimonian-Laird method) was applied when I2 25–75% (moderate heterogeneity). Values >75% were defined as high heterogeneity. If necessary, sensitivity analysis will be performed to evaluate the possible sources of heterogeneity among the studies.
In addition, the Hardy–Weinberg equilibrium (HWE) was calculated using Fisher’s exact test. In meta-analyses of genetic association studies, HWE deviations in controls have been linked to problems in the design and conduct of the studies, mainly due to population stratification, genotyping error, or selection bias.
Publication bias was assessed by Egger’s regression asymmetry test and Begg’s adjusted rank correlation test [14,15], visually displayed in funnel plots. A p-value <0.05 suggested a high probability of publication bias. All statistical analyses were performed in the RStudio® software (version 4.1.0).

3. Results

3.1. Selection and Individual Results of Studies

We identified 2962 articles initially, and 1551 duplicates were removed. In stage I, reading titles and abstracts, 1392 articles did not meet the eligibility criteria. Thus, 19 studies were included in stage II. Nevertheless, three studies were excluded after the complete reading of the manuscript (Figure 1).
From 16 included studies, we had 1 cohort study, 4 cross-sectional studies, and 11 case–control studies. All selected articles were written in English. We identified two studies published in the years 1995, 2001, and 2003, respectively, and one article was published in each of the years 1997, 1998, 2000, 2005, 2006, 2008, 2010, 2014, 2018, and 2021. In this meta-analysis, 2423 (41.95%) individuals with DR (cases) and 3353 (58.05%) individuals without DR (controls) were genotyped. The characteristics of each study can be observed in Table 2. This section may be divided into subheadings. It should provide a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn. This table shows the compiled main data of the 16 eligible studies included in this systematic review.
In addition, the studies were homogeneous in terms of methodological quality assessment, individually reaching a minimum of 70% of positive responses, being considered with a low risk of bias (Table 3). For case–control studies, 9 parameters were evaluated for 8 cohorts and 11 cross-sectional parameters, respectively.
Table 4 describes the genotypic and allelic frequency of ACE gene (I/D) polymorphism found in the case and control groups of the included studies. Additionally, the distribution of genotypes in the control group of the included studies that agreed with the HWE (p = 0.06).

3.2. Meta-Analysis

Meta-analysis was performed with the 16 articles selected in the systematic review. Figure 2 describes a no significant association between the polymorphism and DR risk (OR = 1.12; CI = 0.96–1.31; and p = 0.1359) for genotypic analysis, by the dominant model (II vs. ID+DD). Moreover, we observed also no significant association between the D allele on the allele frequency analysis (I vs. D) and the DR risk (OR = 1.10; CI = 0.98–1.23; and p = 0.1182), Figure 3.
We observed that the larger the sample size the greater the weight of the study and the smaller the CI, indicating greater certainty in the results with a larger sample size (Figure 2 and Figure 3). Small samples may reflect observations due to chance, so the statistical indicators used in meta-analyses, such as CI and individual weight, confirm the degree of reliability of the results.
Our findings showed moderate heterogeneity in the Higgins inconsistency test, which did not interfere with the results obtained. However, we can observe the large variation in sample sizes of the included studies (Table 2), which may reflect the degrees of divergence found. In addition, the funnel plot estimated the publication bias for genotypic comparison (Figure 4) and allelic comparison (Figure 5), and no significant asymmetries were found to identify publication bias.
Egger’s regression asymmetry test and Begg’s adjusted rank correlation test were used to estimate the possible publication bias. Table 5 describes a significant difference in the genotypic comparison with Egger’s test (p = 0.01). However, no other indications of publication bias were found in the studies included in this meta-analysis. Results for a possible publication bias indicated that some studies may underestimate or overestimate the association found, in addition to reflecting a greater facility to publish positive results. However, these results must be interpreted in association with other variables, such as the sample size, study quality, and consistency of the results in independent studies.

4. Discussion

According to the International Diabetes Federation [31], DM affects more than 500 million adults worldwide, aged 20–79 years. The world ranking of countries with the highest number of diabetic adults in 2021 is China, India, and Pakistan [31]. Our systematic review highlighted studies conducted in Japan [16,19,20], United Kingdom [17], Spain [18], Turkey [21,25], Czech Republic [22], Slovenia [23], China [24,30], South Korea [26], Iran [27,28], India [29], and Jordan [5].
DR is one of the most devastating microvascular complications of DM and remains a leading cause of visual morbidity in both developed and developing countries [30]. Furthermore, all ethnicities are affected by DR. On the other hand, studies suggest that African/Afro-Caribbean, South Asian, Latin American, and indigenous tribal populations have relatively higher rates of DR [32]. In this systematic review, we only observed European and Asian studies, making it impossible to characterize and analyze specific genetic factors for each ethnicity, thus revealing the lack of studies analyzing the relationship between ACE gene (I/D) polymorphisms and the DR risk in different populations.
Hyperglycemia in diabetic patients triggers several biochemical processes, leading to inflammation, ischemia, and a pro-angiogenic state in the retina, with subsequent complications of vascular leakage, edema, neovascularization, and neurodegeneration [33,34]. Furthermore, this condition acts as an excitatory stimulus for the renin–Angiotensin–aldosterone system (RAAS), an endocrine hormonal cascade important for regulating blood pressure and hydroelectrolytic homeostasis [4,35]. In addition, the genes of this system play an important role in glucose metabolism [6].
The main components of this system are renin, angiotensinogen (AGT), Angiotensin I and II (Ang I and Ang II), Angiotensin-converting enzymes 1 and 2 (ACE and ACE2), and type 1 (AT1R) and type 2 receptors (AT2R). ACE hyperactivation increases the synthesis of the vasoconstrictor molecule Ang II [36]. Ang II alters glucose homeostasis by inhibiting insulin signal transduction, reducing glucose uptake, increasing insulin resistance, and destroying pancreatic β cells by inducing oxidative stress [37].
Polymorphic variants in genes acting in this system have been correlated with DM and its complications, and RAAS inhibition has reduced the incidence of diseases [6]. Hyperglycemia in DM patients increases Ang II levels, inducing oxidative stress and glomerular hyperfiltration, consequently leading to endothelial damage, thrombosis, inflammation, and vascular remodeling [38]. Abnormal ACE expression in the retina produces adverse effects on retinal blood flow and vascular structure [6]. Therefore, ACE inhibition has been associated with tissue protection of organs to improve ocular function in DM patients, consequently reducing the development and progression of DR [39,40].
Interestingly, ACE gene (I/D) polymorphism is responsible for approximately 50% of the phenotypic variations found in plasma ACE levels, and individuals with the I/I genotype have reduced levels of ACE, whereas I/D individuals have intermediate levels, and D/D individuals have increased levels of the enzyme [8]. Thus, several studies have sought the relationship between RAAS genes and the pathogenesis of DM and its complications, such as DR [41,42,43]. However, the results are still controversial.
Feghhi et al. [27] found a significant association in the I/I vs. D/D comparison (OR = 3516, CI = 1279–9665, and p = 0.015), whereas Nikzamir et al. [28] identified an association in the I/D vs. I/I comparison (OR = 1831, CI = 1074–3124, and p = 0.026) in Iranian patients with T2DM and DR. Furthermore, Matsumoto et al. [20] associated the D allele with the PDR (p = 0.041). Additionally, in Pakistanis, I/D polymorphism was significantly associated with NPDR but not with PDR [43].
Luo et al. [4] performed a meta-analysis evaluating the association between the ACE gene (I/D) polymorphism and the DR risk and found a significant association. Additionally, the authors also described a significant association between the polymorphism studied and the DR risk for all genetic models. However, this study included different types of DM and other complications, such as diabetic nephropathy (DN). Differently, our meta-analysis assessed the susceptibility to DR only in T2DM patients for I/D polymorphism. Previous studies have demonstrated the association of DN with the D allele in this polymorphism [44,45,46], demonstrating a possible selection bias and/or confusion in the meta-analysis performed by Luo et al. [4].
These authors (Luo et al. [4]) still highlighted that ACE gene (I/D) polymorphism appears to be involved in the susceptibility to DR in the Asian population [4]. In contrast, Qiao et al. [30] analyzed 1491 patients with T2DM and was not found an association between ACE gene (I/D) polymorphism and DR in the Chinese population, as well as the other studies included in this systematic review and the meta-analyses performed by [47,48,49]. Another meta-analysis conducted by Zhou et al. [50] also described that the I/D polymorphism was unrelated to the pathogenesis of T2DM in the Chinese population. Considering that most of the studies included in our meta-analysis are from the Asian population, ACE (I/D) polymorphism appears probably not to contribute to DR development, especially in Asian patients with T2DM.
In the context of the non-association between I/D polymorphism and DR, our findings reaffirmed that this polymorphism is not associated with DR susceptibility or with its progression in patients with T2DM. Accordingly, the Higgins inconsistency test did not indicate high heterogeneity between studies. Therefore, we can observe that the studies included in the meta-analysis showed a wide variation in sample size (Table 1), which may reflect the divergence of results found. Thus, when a small sample is used to represent the population of interest, the risk of observations due to chance is greater [51]. In this context, statistical indicators such as the confidence interval and the weight of each study in meta-analyses are used to better determine the degree of certainty of the results. In our data, we can observe that the larger the sample size the greater the weight of the study and the smaller the confidence interval (Figure 2 and Figure 3), indicating greater certainty in results with a larger sample size.
In addition, we found a significant difference in publication bias with Egger’s test for genotypic comparison; the other tests found no significant difference (Begger’s test and funnel plots) (Table 3, Figure 4 and Figure 5). This suggests that the results found in the individual studies may be overestimating or underestimating the true association. However, due to a statistical tool, the results should be interpreted in conjunction with other information, such as sample size, quality of studies, and consistency of results in independent studies. Thus, we highlight the importance of systematic reviews and meta-analyses such as this one, seeking to group, evaluate, and elucidate the true results and possible limitations of genetic association studies.

5. Conclusions

The limitations of this review could be described as (i) different sample sizes found: some of the studies analyzed presented relatively small case–control groups, and the minor allele frequency; (ii) possible publication bias found for genotypic analysis, indicating nonsignificant findings that may exist remaining unpublished, thereby artificially inflating the apparent magnitude of an effect; (iii) ethnicity: in meta-analyses of genetic association studies, ancestry and ethnicity are not accurately investigated; and (iv) the lack of studies evaluating other populations, which limited the possibility to further discussions. However, our findings provided consistent evidence for no associations between ACE gene (I/D) polymorphism and DR risk. Thus, our findings provide subsidies in the area of genetic epidemiology to help in the understanding of the genetic factors involved in the susceptibility to the development of DR.
This systematic review and meta-analysis revealed that ACE gene (I/D) polymorphism appears to be not involved in the susceptibility to DR or with its progression in patients with T2DM. Thus, no evident association was implied with overall DR risk in any genetic models. Additionally, meta-analyses, exploring sensitivity analyses, and possible publication biases are encouraged. The identification of genes and polymorphisms related to the development and progression of T2DM and its complications can help in the early diagnosis and development of effective treatments.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jpm13091308/s1, File S1. Protocol registered in the International Prospective Register of Systematic Reviews (PROSPERO) under number CRD42021291791.

Author Contributions

Conceptualization, R.d.S.S. and A.A.d.S.R.; Methodology, A.R.d.P.C., L.C.S., K.d.F.S., R.d.S.S. and A.A.d.S.R.; Software, K.d.F.S., R.d.S.S. and A.A.d.S.R.; Validation, R.d.S.S. and A.A.d.S.R.; Formal Analysis, A.R.d.P.C., L.C.S. and K.d.F.S.; Investigation, A.R.d.P.C., L.C.S., K.d.F.S., R.d.S.S. and A.A.d.S.R.; Resources, A.R.d.P.C., R.d.S.S. and A.A.d.S.R.; Data Curation, A.R.d.P.C., L.C.S. and K.d.F.S.; Writing—Original Draft Preparation, A.R.d.P.C., K.d.F.S., R.d.S.S. and A.A.d.S.R.; Writing—Review and Editing, A.R.d.P.C., K.d.F.S., R.d.S.S. and A.A.d.S.R.; Supervision, A.A.d.S.R. and R.d.S.S.; Project Administration, A.A.d.S.R.; Funding Acquisition, A.R.d.P.C. and A.A.d.S.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing does not apply to this article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Bourne, R.R.; Stevens, G.A.; White, R.A.; Smith, J.L.; Flaxman, S.R.; Price, H.; Taylor, H.R. Causes of vision loss worldwide, 1990–2010: A systematic analysis. Lancet Glob. Health 2013, 1, e339–e349. [Google Scholar] [CrossRef] [PubMed]
  2. Lechner, J.; O’Leary, O.E.; Stitt, A.W. The pathology associated with diabetic retinopathy. Vis. Res. 2017, 139, 7–14. [Google Scholar] [CrossRef]
  3. Wong, T.Y.; Cheung, C.M.G.; Larsen, M.; Sharma, S.; Simó, R. Diabetic retinopathy. Nat. Rev. Dis. Prim. 2016, 2, 16012. [Google Scholar] [CrossRef]
  4. Luo, S.; Shi, C.; Wang, F.; Wu, Z. Association between the Angiotensin-Converting Enzyme (ACE) Genetic Polymorphism and Diabetic Retinopathy—A Meta-Analysis Comprising 10,168 Subjects. Int. J. Environ. Res. Public Health 2016, 13, 1142. [Google Scholar] [CrossRef] [PubMed]
  5. Abu-Hassan, D.W.; Al-Bdour, M.D.; El-Khateeb, M. Lack of relationship between Alu repetitive elements in angiotensin converting enzyme and the severity of diabetic retinopathy. J. Med. Biochem. 2021, 40, 302–309. [Google Scholar]
  6. Rahimi, Z.; Moradi, M.; Nasri, H. A systematic review of the role of renin angiotensin aldosterone system genes in diabetes mellitus, diabetic retinopathy and diabetic neuropathy. J. Res. Med. Sci. 2014, 19, 1090–1098. [Google Scholar]
  7. Sayed-Tabatabaei, F.A.; Oostra, B.A.; Isaacs, A.; van Duijn, C.M.; Witteman, J.C.M. ACE Polymorphisms. Circ. Res. 2006, 98, 1123–1133. [Google Scholar] [CrossRef]
  8. Rigat, B.; Hubert, C.; Alhenc-Gelas, F.; Cambien, F.; Corvol, P.; Soubrier, F. An insertion/deletion polymorphism in the angiotensin I-converting enzyme gene accounting for half the variance of serum enzyme levels. J. Clin. Investig. 1990, 86, 1343–1346. [Google Scholar] [CrossRef]
  9. Rahimi, Z.; Hasanvand, A.; Felehgari, V. Interaction of MTHFR 1298C with ACE D allele augments the risk of diabetic nephropathy in Western Iran. DNA Cell Biol. 2012, 31, 553–559. [Google Scholar] [CrossRef] [PubMed]
  10. Williams, D.M.; Nawaz, A.; Evans, M. Diabetes and Novel Coronavirus Infection: Implications for Treatment. Diabetes Ther. 2020, 11, 1915–1924. [Google Scholar] [CrossRef]
  11. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Moher, D. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021, 372, 71. [Google Scholar] [CrossRef] [PubMed]
  12. Ouzzani, M.; Hammady, H.; Fedorowicz, Z.; Elmagarmid, A. Rayyan–a web and mobile app for systematic reviews. Syst. Rev. 2016, 5, 210. [Google Scholar] [CrossRef]
  13. Institute, TJB. JBI Reviewer’s Manual. Joanna Briggs Inst. 32. The Joanna Briggs Institute. 2022. Available online: https://reviewersmanual.joannabriggs.org/ (accessed on 20 March 2023).
  14. Begg, C.B.; Mazumdar, M. Operating characteristics of a rank correlation test for publication bias. Biometrics 1994, 50, 1088–1101. [Google Scholar] [CrossRef] [PubMed]
  15. Egger, M.; Davey Smith, G.; Schneider, M.; Minder, C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997, 315, 629–634. [Google Scholar] [CrossRef] [PubMed]
  16. Fujisawa, T.; Ikegami, H.; Shen, G.-Q.; Yamato, E.; Takekawa, K.; Nakagawa, Y.; Ogihara, T. Angiotensin I-converting enzyme gene polymorphism is associated with myocardial infarction, but not with retinopathy or nephropathy, in NIDDM. Diabetes Care 1995, 18, 983–985. [Google Scholar] [CrossRef]
  17. Nagi, D.K.; Mansfield, M.W.; Stickland, M.H.; Grant, P.J. Angiotensin converting enzyme (ACE) insertion/deletion (I/D) polymorphism, and diabetic retinopathy in subjects with IDDM and NIDDM. Diabet. Med. 1995, 12, 997–1001. [Google Scholar] [CrossRef]
  18. Gutiérrez, C.; Vendrell, J.; Pastor, R.; Llor, C.; Aguilar, C.; Broch, M.; Richart, C. Angiotensin I-converting enzyme and angiotensinogen gene polymorphisms in non-insulin-dependent diabetes mellitus. Lack of relationship with diabetic nephropathy and retinopathy in a Caucasian Mediterranean population. Metabolism 1997, 46, 976–980. [Google Scholar] [CrossRef]
  19. Hanyu, O.; Hanawa, H.; Nakagawa, O.; Tani, N.; Andou, N.; Aizawa, Y.; Shibata, A. Polymorphism of the angiotensin I-converting enzyme gene in diabetic nephropathy in type II diabetic patients with proliferative retinopathy. Ren. Fail. 1998, 20, 125–133. [Google Scholar] [CrossRef]
  20. Matsumoto, A.; Iwashima, Y.; Abiko, A.; Morikawa, A.; Sekiguchi, M.; Eto, M.; Makino, I. Detection of the association between a deletion polymorphism in the gene encoding angiotensin I-converting enzyme and advanced diabetic retinopathy. Diabetes Res. Clin. Pract. 2000, 50, 195–202. [Google Scholar] [CrossRef]
  21. Araz, M.; Yilmaz, N.; Güngör, K.; Okan, V.; Kepekci, Y.; Sükrü Aynacioglu, A. Angiontensin-converting enzyme gene polymorphism and microvascular complications in Turkish type 2 diabetic patients. Diabetes Res. Clin. Pract. 2001, 54, 95–104. [Google Scholar] [CrossRef]
  22. Kanková, K.; Muzík, J.; Karásková, J.; Beránek, M.; Hájek, D.; Znojil, V.; Vácha, J. Duration of non-insulin-dependent diabetes mellitus and the TNF-beta NcoI genotype as predictive factors in proliferative diabetic retinopathy. Ophthalmologica 2001, 215, 294–298. [Google Scholar] [CrossRef]
  23. Globocnik-Petrovic, M.; Hawlina, M.; Peterlin, B.; Petrovic, D. Insertion/deletion plasminogen activator inhibitor 1 and insertion/deletion angiotensin-converting enzyme gene polymorphisms in diabetic retinopathy in type 2 diabetes. Ophthalmologica 2003, 217, 219–224. [Google Scholar] [CrossRef] [PubMed]
  24. Thomas, G.N.; Critchley, J.A.J.H.; Tomlinson, B.; Yeung, V.T.F.; Lam, D.; Cockram, C.S. Renin-angiotensin system gene polymorphisms and retinopathy in Chinese patients with type 2 diabetes. Diabetes Care 2003, 26, 1643–1644. [Google Scholar] [CrossRef]
  25. Degirmenci, I.; Kebapci, N.; Basaran, A.; Efe, B.; Gunes, H.V.; Akalin, A.; Demirustu, C. Frequency of angiotensin-converting enzyme gene polymorphism in Turkish type 2 diabetic patients. Int. J. Clin. Pract. 2005, 59, 1137–1142. [Google Scholar] [CrossRef] [PubMed]
  26. Lee, S.J.; Choi, M.G. Association of manganese superoxide dismutase gene polymorphism (V16A) with diabetic macular edema in Korean type 2 diabetic patients. Metabolism 2006, 55, 1681–1688. [Google Scholar] [CrossRef]
  27. Feghhi, M.; Nikzamir, A.; Esteghamati, A.; Farahi, F.; Nakhjavani, M.; Rashidi, A. The relationship between angiotensin-converting enzyme insertion/deletion polymorphism and proliferative retinopathy in type 2 diabetes. Diabetes Res. Clin. Pract. 2008, 81, e1–e4. [Google Scholar] [CrossRef]
  28. Nikzamir, A.; Rashidi, A.; Esteghamati, A.; Nakhjavani, M.; Golmohammadi, T.; Khalilzadeh, O. The relationship between ACE gene insertion/deletion polymorphism and diabetic retinopathy in Iranian patients with type 2 diabetes. Ophthalmic Genet. 2010, 31, 108–113. [Google Scholar] [CrossRef] [PubMed]
  29. Narne, P.; Ponnaluri, K.C.; Siraj, M.; Ishaq, M. Association analysis of polymorphisms in genes related to oxidative stress in South Indian type 2 diabetic patients with retinopathy. Ophthalmic Genet. 2016, 37, 1–8. [Google Scholar] [CrossRef]
  30. Qiao, Y.-C.; Wang, M.; Pan, Y.-H.; Zhang, X.-X.; Tian, F.; Chen, Y.-L.; Zhao, H.L. The relationship between ACE/AGT gene polymorphisms and the risk of diabetic retinopathy in Chinese patients with type 2 diabetes. J. Renin-Angiotensin-Aldosterone Syst. 2018, 19, 1470320317752955. [Google Scholar] [CrossRef]
  31. IDF. International Diabetes Federation. Diabetes. In Atlas of Diabetes, 10a ed.; Boyko, E.J., Magliano, D.J., Eds.; Science & Business Media: Brussels, Belgium, 2021. [Google Scholar]
  32. Hampton, B.M.; Schwartz, S.G.; Brantley, M.A.; Flynn, H.W. Update on genetics and diabetic retinopathy. Clin. Ophthalmol. 2015, 9, 2175–2193. [Google Scholar]
  33. Suzuki, Y.; Kiyosawa, M. Relationship between Diabetic Nephropathy and Development of Diabetic Macular Edema in Addition to Diabetic Retinopathy. Biomedicines 2023, 11, 1502. [Google Scholar] [CrossRef]
  34. Vofo, B.N.; Chowers, I. Suppressing Inflammation for the Treatment of Diabetic Retinopathy and Age-Related Macular Degeneration: Dazdotuftide as a Potential New Multitarget Therapeutic Candidate. Biomedicines 2023, 11, 1562. [Google Scholar] [CrossRef] [PubMed]
  35. Wang, F.; Fang, Q.; Yu, N.; Zhao, D.; Zhang, Y.; Wang, J.; Fan, X. Association between genetic polymorphism of the angiotensin-converting enzyme and diabetic nephropathy: A meta-analysis comprising 26,580 subjects. J. Renin-Angiotensin-Aldosterone Syst. 2012, 13, 161–174. [Google Scholar] [CrossRef]
  36. Silveira, L.C.; da Silva, E.G.; Azevedo, R.M.; dos Anjos, L.R.B.; Chagas, R.F.; Alcântara, E.C.; Reis, A.A.S. ACE insertion/deletion polymorphism and diabetic nephropathy: An evidence-based meta-analysis. Genet. Mol. Res. 2019, 18, GMR18378. [Google Scholar] [CrossRef]
  37. Zhou, M.S.; Schulman, I.H. Prevention of diabetes in hypertensive patients: Results and implications from the VALUE trial. Vasc. Health Risk Manag. 2009, 5, 361–368. [Google Scholar] [CrossRef] [PubMed]
  38. Rahimi, Z.; Mansouri, Z.O.; Rahimi, Z.; Abbasi, A. AT2R -1332 G: A polymorphism and diabetic nephropathy in type 2 diabetes mellitus patients. J. Ren. Inj. Prev. 2013, 2, 97–101. [Google Scholar]
  39. Cordonnier, D.J.; Zaoui, P.; Halimi, S. Role of ACE inhibitors in patients with diabetes mellitus. Drugs 2001, 61, 1883–1892. [Google Scholar] [CrossRef]
  40. Gilbert, R.E.; Krum, H.; Wilkinson-Berka, J.; Kelly, D.J. The renin-angiotensin system and the long-term complications of diabetes: Pathophysiological and therapeutic considerations. Diabet. Med. 2003, 20, 607–621. [Google Scholar] [CrossRef] [PubMed]
  41. Yildiz, M.; Karkucak, M.; Yakut, T.; Gorukmez, O.; Ozmen, A. Lack of association of genetic polymorphisms of angiotensin-converting enzyme gene I/D and glutathione-S-transferase enzyme T1 and M1 with retinopathy of prematures. Genet. Mol. Res. 2010, 9, 2131–2139. [Google Scholar] [CrossRef]
  42. Cheema, B.S.; Kohli, H.S.; Sharma, R.; Shah, V.N.; Bhansali, A.; Khullar, M. Angiotensin-converting enzyme gene variants interact with the renin-angiotensin system pathway to confer risk and protection against type 2 diabetic retinopathy. J. Diabetes Investig. 2013, 4, 103–104. [Google Scholar] [CrossRef]
  43. Saleem, S.; Azam, A.; Maqsood, S.I.; Muslim, I.; Bashir, S.; Fazal, N.; Azam, M. Role of ACE and PAI-1 Polymorphisms in the Development and Progression of Diabetic Retinopathy. PLoS ONE 2015, 10, e0144557. [Google Scholar] [CrossRef]
  44. Schmidt, S.; Strojek, K.; Grzeszczak, W.; Bergis, K.; Ritz, E. Excess of DD homozygotes in haemodialysed patients with type II diabetes. The diabetic nephropathy study group. Nephrol. Dial. Transpl. 1997, 12, 427–429. [Google Scholar] [CrossRef] [PubMed]
  45. Shaker, O.G.; Ismail, M.F.; Ashour, E.; Yousif, H.M.; Afify, M.; Gouda, W. ACE gene polymorphism and serum ACE level with Progression of Nephropathy in Type 2 Diabetic Patients. J. Adv. Chem. 2014, 9, 2023–2032. [Google Scholar] [CrossRef]
  46. Alharbi, A.M.D.; Alhazmi, A.M.S. Prevalence, Risk Factors, and Patient Awareness of Diabetic Retinopathy in Saudi Arabia: A Review of the Literature. Cureus 2020, 12, e11991. [Google Scholar] [CrossRef] [PubMed]
  47. Abhary, S.; Hewitt, A.W.; Burdon, K.P.; Craig, J.E. A systematic meta-analysis of genetic association studies for diabetic retinopathy. Diabetes 2009, 58, 2137–2147. [Google Scholar] [CrossRef]
  48. Salem, A.H.; Batzer, M.A. High frequency of the D allele of the angiotensin converting enzyme gene in Arabic populations. BMC Res. Notes 2009, 2, 99. [Google Scholar] [CrossRef]
  49. Zhou, J.B.; Yang, J.K. Angiotensin-converting enzyme gene polymorphism is associated with proliferative diabetic retinopathy: A meta-analysis. Acta Diabetol. 2010, 47 (Suppl. 10), 187–193. [Google Scholar] [CrossRef]
  50. Zhou, D.; Ruiter, R.; Zhang, J.; Zhou, M.; Liu, H.; Liu, W.; Wang, S. Angiotensin-converting enzyme I/D polymorphism is not associated with type 2 diabetes in a Chinese population. JRAAS–J. Renin-Angiotensin-Aldosterone Syst. 2012, 13, 372–378. [Google Scholar] [CrossRef]
  51. Catalogue of Bias Collaboration; Spencer, E.A.; Brassey, J.; Mahtani, K.; Heneghan, C. Wrong sample size bias. In Catalogue of Bias; 2017; Available online: https://catalogofbias.org/biases/wrong-sample-size-bias/ (accessed on 20 March 2023).
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Figure 1. PRISMA flowchart detailing the selection process of the articles included and excluded in this systematic review and meta-analysis.
Figure 1. PRISMA flowchart detailing the selection process of the articles included and excluded in this systematic review and meta-analysis.
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Figure 2. Forest plot for genotypic comparison (II vs. ID+DD). The odds ratio (OR) and 95% confidence interval (95% CI) were calculated using the DerSimonian–Laird method (random effect model) due to the Higgins inconsistency test (I2) value. Abu-Hassan et al. 2021 [5], Fujisawa et al. 1995 [16], Nagi et al. 1995 [17], Gutierrez et al. 1997 [18], Hanyu et al. 1998 [19], Matsumoto et al. 2000 [20], Araz et al. 2001 [21], Kankova et al. 2001 [22], Globocnik-Petrovic et al. 2003 [23], Thomas et al. 2003 [24], Degirmenci et al. 2005 [25], Lee; Choi 2006 [26], Feghhi et al. 2008 [27], Nikzamir et al. 2010 [28], Narne et al. 2014 [29], Qiao et al. 2018 [30].
Figure 2. Forest plot for genotypic comparison (II vs. ID+DD). The odds ratio (OR) and 95% confidence interval (95% CI) were calculated using the DerSimonian–Laird method (random effect model) due to the Higgins inconsistency test (I2) value. Abu-Hassan et al. 2021 [5], Fujisawa et al. 1995 [16], Nagi et al. 1995 [17], Gutierrez et al. 1997 [18], Hanyu et al. 1998 [19], Matsumoto et al. 2000 [20], Araz et al. 2001 [21], Kankova et al. 2001 [22], Globocnik-Petrovic et al. 2003 [23], Thomas et al. 2003 [24], Degirmenci et al. 2005 [25], Lee; Choi 2006 [26], Feghhi et al. 2008 [27], Nikzamir et al. 2010 [28], Narne et al. 2014 [29], Qiao et al. 2018 [30].
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Figure 3. Forest plot for allelic comparison (I vs. D). The odds ratio (OR) and 95% confidence interval (95% CI) were calculated using the DerSimonian–Laird method (random effect model) due to the Higgins inconsistency test (I2) value. Abu-Hassan et al. 2021 [5], Fujisawa et al. 1995 [16], Nagi et al. 1995 [17], Gutierrez et al. 1997 [18], Hanyu et al. 1998 [19], Matsumoto et al. 2000 [20], Araz et al. 2001 [21], Kankova et al. 2001 [22], Globocnik-Petrovic et al. 2003 [23], Thomas et al. 2003 [24], Degirmenci et al. 2005 [25], Lee; Choi 2006 [26], Feghhi et al. 2008 [27], Nikzamir et al. 2010 [28], Narne et al. 2014 [29], Qiao et al. 2018 [30].
Figure 3. Forest plot for allelic comparison (I vs. D). The odds ratio (OR) and 95% confidence interval (95% CI) were calculated using the DerSimonian–Laird method (random effect model) due to the Higgins inconsistency test (I2) value. Abu-Hassan et al. 2021 [5], Fujisawa et al. 1995 [16], Nagi et al. 1995 [17], Gutierrez et al. 1997 [18], Hanyu et al. 1998 [19], Matsumoto et al. 2000 [20], Araz et al. 2001 [21], Kankova et al. 2001 [22], Globocnik-Petrovic et al. 2003 [23], Thomas et al. 2003 [24], Degirmenci et al. 2005 [25], Lee; Choi 2006 [26], Feghhi et al. 2008 [27], Nikzamir et al. 2010 [28], Narne et al. 2014 [29], Qiao et al. 2018 [30].
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Figure 4. Funnel plot for the publication bias of the studies included in the meta-analysis in the genotypic comparison (II vs. ID+DD). Each square represents a study included in the meta-analysis.
Figure 4. Funnel plot for the publication bias of the studies included in the meta-analysis in the genotypic comparison (II vs. ID+DD). Each square represents a study included in the meta-analysis.
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Figure 5. Funnel plot for the publication bias of the studies included in the meta-analysis in the allelic comparison (I vs. D). Each square represents a study included in the meta-analysis.
Figure 5. Funnel plot for the publication bias of the studies included in the meta-analysis in the allelic comparison (I vs. D). Each square represents a study included in the meta-analysis.
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Table 1. Search strategies elaborated for Systematic Review.
Table 1. Search strategies elaborated for Systematic Review.
DatabasesSearch Strategy
PubMed/MEDLINE((“Diabetes Mellitus”[Mesh] OR “Diabetes Mellitus, Type 2”[Mesh]) AND (“Polymorphism, Genetic”[Mesh] OR “Amplified Fragment Length Polymorphism Analysis”[Mesh])) AND (“Diabetic Retinopathy/complications”[Mesh] OR “Diabetic Retinopathy/genetics”[Mesh])
Embase‘((‘diabetes mellitus’/exp OR ‘non insulin dependent diabetes mellitus’/exp) AND ‘genetic polymorphism’/exp OR ‘amplified fragment length polymorphism’/exp) AND ‘diabetic retinopathy’/exp AND [1992–2022]/py
Web of Science((((ALL=(diabetes)) OR ALL=(type 2 diabetes mellitus)) AND ALL=(genetic polymorphism)) OR ALL=(amplified fragment length polymorphism analysis)) AND ALL=(diabetic retinopathy)
Scopus(TITLE-ABS-KEY (diabetes) OR TITLE-ABS-KEY (type 2 diabetes AND mellitus) AND TITLE-ABS-KEY (genetic AND polymorphism) OR TITLE-ABS-KEY (amplified AND fragment AND length AND polymorphism AND analysis) AND TITLE-ABS-KEY (diabetic AND retinopathy)) AND (LIMIT-TO (PUBYEAR, 2022) OR LIMIT-TO (PUBYEAR, 2021) OR LIMIT-TO (PUBYEAR, 2020) OR LIMIT-TO (PUBYEAR, 2019) OR LIMIT-TO (PUBYEAR, 2018) OR LIMIT-TO (PUBYEAR, 2017) OR LIMIT-TO (PUBYEAR, 2016) OR LIMIT-TO (PUBYEAR, 2015) OR LIMIT-TO (PUBYEAR, 2014) OR LIMIT-TO (PUBYEAR, 2013) OR LIMIT-TO (PUBYEAR, 2012) OR LIMIT-TO (PUBYEAR, 2011) OR LIMIT-TO (PUBYEAR, 2010) OR LIMIT-TO (PUBYEAR, 2009) OR LIMIT-TO (PUBYEAR, 2008) OR LIMIT-TO (PUBYEAR, 2007) OR LIMIT-TO (PUBYEAR, 2006) OR LIMIT-TO (PUBYEAR, 2005) OR LIMIT-TO (PUBYEAR, 2004) OR LIMIT-TO (PUBYEAR, 2003) OR LIMIT-TO (PUBYEAR, 2002) OR LIMIT-TO (PUBYEAR, 2001) OR LIMIT-TO (PUBYEAR, 2000) OR LIMIT-TO (PUBYEAR, 1999) OR LIMIT-TO (PUBYEAR, 1998) OR LIMIT-TO (PUBYEAR, 1997) OR LIMIT-TO (PUBYEAR, 1996) OR LIMIT-TO (PUBYEAR, 1995) OR LIMIT-TO (PUBYEAR, 1994) OR LIMIT-TO (PUBYEAR, 1993) OR LIMIT-TO (PUBYEAR, 1992))
Table 2. Characteristics of studies included in the systematic review and meta-analysis.
Table 2. Characteristics of studies included in the systematic review and meta-analysis.
ReferenceCountryDesignCaseControl
Sample SizeSex (M/F)Age (Year)DM Duration (Year)DefinitionSample SizeSex (M/F)Age (Year)DM Duration (Year)Definition
Abu-Hassan et al. [5]JordanCross-sectional8041/4162 ± 810.8 ± 4.1DR (T2DM)10039/6160 ± 87.0 ± 4.3NDR (T2DM)
Fujisawa et al. [16]JapanCase-control222NANANADR (T2DM)45NANANANDR (T2DM)
Nagi et al. [17]United KingdomCross-sectional17755/4566.8 ± 10.411 (1–36)DR (T2DM)18652/4869.5 ± 11.17 (1–45)NDR (T2DM)
Gutiérrez et al. [18]SpainCase-control6829/3961.90 ± 9.114.8 ± 5.7DR (T2DM)9245/4759.6 ± 10.312.1 ± 6.3NDR (T2DM)
Hanyu et al. [19]JapanCase-control4515/3058.0 ± 8.818.2 ± 5.7DR (T2DM)5731/2656.4 ± 5.1NAHealthy
Matsumoto et al. [20]JapanCase-control6027/3756.8±11.9016.2 ± 9.1DR (T2DM)9050/4058.9 ± 12.115.0 ± 6.6NDR (T2DM)
Araz et al. [21]TurkeyCross-sectional12049/7155 ± 811.2 ± 6.5DR (T2DM)11937/8251 ± 95.2 ± 5.1NDR (T2DM)
Kanková et al. [22]Czech RepublicCohort246118/12864.1 ± 11.110.2 ± 9.2DR (T2DM)17667/10963.60 ± 13.4NAHealthy
Globocnik-Petrovic et al. [23]SloveniaCase-control12459/6565.6 ± 9.718.7 ± 9.1DR (T2DM)8040/4071.3 ± 7.016.8 ± 6.8NDR (T2DM)
Thomas et al. [24]ChinaCase-control326128/19859.8 ± 11.46.3 (5.6–7.0)DR (T2DM)501197/30460.4 ± 9.36.0 (5.6–6.3)NDR (T2DM)
Degirmenci et al. [25]TurkeyCase-control5795/4857.66 ± 0.8510.64 ± 0.22DR (T2DM)8383/5046.39 ± 1.52NANDR (T2DM)
Lee; Choi [26]South KoreaCross-sectional13077/5353.1 ± 12.311.4 ± 3.7DR (T2DM)174102/7253.7 ± 12.99.4.± 2.8NDR (T2DM)
Feghhi et al. [27]IranCase-control9456/3860.55 ± 8.1514.01 ± 4.38PDR (T2DM)13687/4960.46 ± 7.8513.40 ± 5.0NPDR (T2DM)
Nikzamir et al. [28]IranCase-control17892/8659.0 ± 8.713 (4–30)DR (T2DM)206114/9259.5 ± 8.211 (1–30)NDR (T2DM)
Narne et al. [29]IndiaCase-control14947/10252.7 ± 7.314.7 ± 4.7DR (T2DM)16249/11353.4 ± 5.415.9 ± 5.6NDR (T2DM)
Qiao et al. [30]ChinaCross-sectional344148/19760.08 ±11.348.97 ±7.13DR (T2DM)1141455/69151.42 ±13.594.45 ±4.62NDR (T2DM)
DM: Diabetes mellitus; DR: diabetic retinopathy; F: female; M: male; NA, not available; NPDR: non-proliferative diabetic retinopathy; NDR: No diabetic retinopathy; PDR: proliferative diabetic retinopathy; and T2DM: type 2 diabetes mellitus.
Table 3. Summary of responses for each study included in the risk of bias assessment.
Table 3. Summary of responses for each study included in the risk of bias assessment.
ReferenceQ1Q2Q3Q4Q5Q6Q7Q8Q9Q10Q11
Abu-Hassan et al. [5] 2YYNYYUYYNANANA
Fujisawa et al. [15] 1YYYYYNNYYYNA
Nagi et al. [17] 2YYYYYUYYNANANA
Gutiérrez et al. [18] 1YYYYYYYYYYNA
Hanyu et al. [19] 1YYYYYYYYYYNA
Matsumoto et al. [20] 1YYYYYYYYYYNA
Araz et al. [21] 2YYYYYYYYNANANA
Kanková et al. [22] 3YYYYYUYYYNAY
Globocnik-Petrovic et al. [23] 1YYYYYYYYYYNA
Thomas et al. [24] 1YYUYYYNYYYNA
Degirmenci et al. [25] 1YYYYYYYYYYNA
Lee; Choi [26] 2YYYYYYYYNANANA
Feghhi et al. [27] 1YYYYYYYYYYNA
Nikzamir et al. [28] 1YYYYYYYYYYNA
Narne et al. [29] 1YYYYYYYYYYNA
Qiao et al. [30] 2YYYYYYYYNANANA
1 Case-control; 2 Cross-sectional; 3 Cohort. N—No; NA—Not applicable; U—Unclear; Q—Question; and Y—Yes.
Table 4. Genotypic and allelic frequencies of the ACE gene (I/D) polymorphism were included in the systematic review and meta-analysis.
Table 4. Genotypic and allelic frequencies of the ACE gene (I/D) polymorphism were included in the systematic review and meta-analysis.
ReferenceGenotype FrequencyAllele Frequency
I/II/DD/DID
CaseControlCaseControlCaseControlCaseControlCaseControl
Abu-Hassan et al. [5]304841399131011355965
Fujisawa et al. [16]8719102203362765816832
Nagi et al. [17]474381894954175175179197
Gutiérrez et al. [18]61430443234427294112
Hanyu et al. [19]2117182761360613053
Matsumoto et al. [20]163527401715591106170
Araz et al. [21]202162593839102101138137
Kanková et al. [22]4841135906345231172261180
Globocnik-Petrovic et al. [23]2823633233251197812982
Thomas et al. [24]1572311292124058443674209328
Degirmenci et al. [25]6193439172546736889
Lee; Choi [26]47676968143916320297146
Feghhi et al. [27]15354582341975152113120
Nikzamir et al. [28]4756731105840167222189190
Narne et al. [29]466476662732168194130130
Qiao et al. [30]164510138507421244661527222755
Total7851243112315245125812693400621472686
D: Deletion; and I: Insertion.
Table 5. Publication bias test results for genotypic and allelic analyses.
Table 5. Publication bias test results for genotypic and allelic analyses.
Analyzes PerformedEgger’s TestBegg’s Test
Genotypic0.010.05
Allelic0.250.27
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Coelho, A.R.d.P.; Silveira, L.C.; Santos, K.d.F.; Santos, R.d.S.; Reis, A.A.d.S. No Association of Angiotensin-Converting Enzyme Insertion/Deletion (ACE I/D) Gene Polymorphism in the Susceptibility to Diabetic Retinopathy in Type 2 Diabetes Mellitus Patients: An Updated Meta-Analysis. J. Pers. Med. 2023, 13, 1308. https://doi.org/10.3390/jpm13091308

AMA Style

Coelho ARdP, Silveira LC, Santos KdF, Santos RdS, Reis AAdS. No Association of Angiotensin-Converting Enzyme Insertion/Deletion (ACE I/D) Gene Polymorphism in the Susceptibility to Diabetic Retinopathy in Type 2 Diabetes Mellitus Patients: An Updated Meta-Analysis. Journal of Personalized Medicine. 2023; 13(9):1308. https://doi.org/10.3390/jpm13091308

Chicago/Turabian Style

Coelho, Aline Ruilowa de Pinho, Luciana Carvalho Silveira, Kamilla de Faria Santos, Rodrigo da Silva Santos, and Angela Adamski da Silva Reis. 2023. "No Association of Angiotensin-Converting Enzyme Insertion/Deletion (ACE I/D) Gene Polymorphism in the Susceptibility to Diabetic Retinopathy in Type 2 Diabetes Mellitus Patients: An Updated Meta-Analysis" Journal of Personalized Medicine 13, no. 9: 1308. https://doi.org/10.3390/jpm13091308

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