The Associations between Paraoxonase 1 L55M/Q192R Genetic Polymorphisms and the Susceptibilities of Diabetic Macroangiopathy and Diabetic Microangiopathy: A Meta-Analysis

We carried out literature searches for papers published in English or Chinese in the Embase, PubMed, Wanfang Database, and China National Knowledge Internet (CNKI) databases using the following keywords: “PON1” or “paraoxonase 1,” “diabetes” or “diabetes mellitus” or “DM” or “Type 2 diabetes mellitus (T2DM)” or “Type 1 diabetes mellitus (T1DM),” and “variation” or “polymorphism” or “single nucleotide polymorphism” or “SNP.” We also searched through relevant articles manually to find additional reports.

Articles were included in this meta-analysis if they complied with the following criteria: (1) they were published as original case–control studies; (2) they reported the relationship(s) of paraoxonase 1 L55M and/or Q192R genetic polymorphisms with diabetic macroangiopathy and/or diabetic microangiopathy susceptibility; (3) they used DM without any complication as a control. When the same series of patients were used in more than one article, we used the latest and most complete study.

WCF and WDL screened all of the articles found in the searches and extracted data from all eligible publications independently. For each study included in our meta-analysis, we carefully extracted the following information: first author, published year, country, ethnicity, type of DM, diagnostic criteria used for diabetic complications, and paraoxonase 1 L55M and/or Q192R genotypes in each group. If there were any discrepancies between the data extracted by WCF and WDL, they attempted to resolve the disagreement through discussion; if no agreement was reached, another author was consulted to resolve the dispute.

This article is based on previously conducted studies and does not contain any studies with human participants or animals performed by any of the authors.

Our meta-analysis followed the recommendations of the PRISMA statement and used the Newcastle–Ottawa Scale (NOS) criteria to assess study quality. Studies that met five or more of the NOS criteria were considered of high quality. Pooled odds ratios (ORs) were used to explore the relationships of paraoxonase 1 L55M and Q192R polymorphisms with the susceptibilities to diabetic macroangiopathy and/or diabetic microangiopathy. Heterogeneity was measured using the chi-square-based Q test. A random effects model was applied when I² > 50% and P < 0.05. Otherwise, a fixed effects model was used. Publication bias was investigated using Egger’s test and a funnel plot. This meta-analysis was performed using STATA 12.0 software (Stata Corporation, TX, USA). P < 0.05 was taken to imply statistical significance.

As shown in Fig. S1 of the Electronic supplementary material (ESM), 332 publications were identified, among which 111 duplicates and 57 irrelevant papers were subsequently excluded. Of the remaining 164 papers, 139 were excluded for the following reasons: the paper was a review, no diabetic macroangiopathy or microangiopathy groups were included, there was no DM without complication group, the paper was a duplicate, and other paraoxonase 1 genetic polymorphisms were studied. Thus, 25 articles were ultimately included in the present meta-analysis. Eleven publications were written in English [8‐18] and 14 were written in Chinese [19‐32]. Table 1 shows detailed information on those 25 studies. The name of the first author, the year published, country, ethnicity, the type of DM, the numbers and ages of the cases and controls, the diagnostic criteria used for diabetic complications, and the genetic polymorphisms of paraoxonase 1 studied in each work are presented. All studies were found to be of high quality according to the NOS criteria.

As shown in Table 2, six studies probed the association between paraoxonase 1 L55M genetic polymorphism and the risk of diabetic macroangiopathy; these studies included 431 cases and 640 DM patients without complications as the control. Two studies were performed in Europe [10, 17], and four were carried out in Asia [9, 16, 31, 32]. The results indicated that there was no heterogeneity in the dominant model (LM + MM vs LL: I² = 0.0%, P = 0.447, Fig. 1a, Table 4), homozygous model (MM vs LL: I² = 30.7%, P = 0.217, Fig. 1b, Table 4), allelic contrast model (M vs L: I² = 16.8%, P = 0.305, Fig. 1c, Table 4), recessive model (MM vs LL + LM: I² = 19.9%, P = 0.288, Fig. 1d, Table 4), and heterozygous model (LM vs LL: I² = 0.0%, P = 0.610, Fig. 1e, Table 4). Meta-analysis suggested that there was no significant association of paraoxonase 1 L55M genetic polymorphism with susceptibility to diabetic macroangiopathy in all five models (LM + MM vs LL: OR 0.98, 95% CI 0.69–1.38, P = 0.996, Fig. 1a; MM vs LL: OR 1.30, 95% CI 0.81–2.08, P = 0.279, Fig. 1b; and M vs L: OR 1.10, 95% CI 0.87–1.39, P = 0.414, Fig. 1c; MM vs LLLM: OR 1.30, 95% CI 0.99–1.90, P = 0.176, Fig. 1d; LM vs LL: OR 0.90, 95% CI 0.62–1.30, P = 0.569, Fig. 1e; Table 4). When the effects models were altered, the significances of these three models did not change statistically significantly (data not shown). Based on the funnel plot and Egger’s test, none of the three models had significant publication bias (LM + MM vs LL: t = − 0.040, P = 0.970; MM vs LL: t = 0.300, P = 0.781; M vs L: t = − 0.340, P = 0.752; MM vs LL + LM: t = 0.69, P = 0.539; LM vs LL: t = − 0.10, P = 0.923; data not shown).

As shown in Table 2, nine studies focused on the association of paraoxonase 1 L55M genetic polymorphism with the risk of diabetic microangiopathy; these studies included 992 cases and 1212 controls [8, 10, 12, 13, 15, 17‐19, 30]. The results showed that there was significant heterogeneity in the dominant model (LM + MM vs LL: I² = 81.0%, P = 0.000, Fig. 2a, Table 4), homozygous model (MM vs LL: I² = 80.9%, P = 0.000, Fig. 2b, Table 4), allelic contrast model (M vs L: I² = 84.1%, P = 0.000, Fig. 2c, Table 4), recessive model (MM vs LL + LM: I² = 68.6%, P = 0.001, Fig. 2d, Table 4), and heterozygous model (LM vs LL: I² = 71.1%, P = 0.000, Fig. 2e, Table 4). Thus, subgroup analysis of ethnicity, type of DM, and Hardy–Weinberg equilibrium (HWE) was performed, and the results indicated that ethnicity and type of DM can explain the heterogeneity in the recessive model, but not the heterogeneity in the other models (Table 4). Meta-regression analysis was then performed using the covariates published year, sample size, ethnicity, type of DM, and HWE to investigate the sources of the between-study heterogeneity, but it failed to identify those sources (Table 5). Paraoxonase 1 L55M genetic polymorphism was clearly related to diabetic microangiopathy susceptibility in the dominant model (OR 0.53, 95% CI 0.33–0.83, P = 0.006, Fig. 2a, Table 4), the homozygous model (OR 0.37, 95% CI 0.16–0.86, P = 0.021, Fig. 2b, Table 4), the allelic contrast model (OR 0.62, 95% CI 0.43–0.90, P = 0.011, Fig. 2c, Table 4), the recessive model (OR 12.04, 95% CI 8.02–18.06, P = 0.000, Fig. 2d, Table 4), and the heterozygous model (OR 0.57, 95% CI 0.38–0.85, P = 0.006, Fig. 2e, Table 4). When the effects models were changed, the statistical significance did not alter (data not shown). Meanwhile, the funnel plot and Egger’s test indicated that there was no significant publication bias in the models (LM + MM vs LL: t = − 0.640, P = 0.543; MM vs LL: t = − 1.750, P = 0.124; M vs L: t = − 0.710, P = 0.503; LM vs LL: t = − 0.540, P = 0.607; data not shown) except for the recessive model (MM vs LL + LM: t = 2.580, P = 0.037, data not shown).

As shown in Table 3, twelve studies focused on the association of paraoxonase 1 Q192R genetic polymorphism with the risk of diabetic macroangiopathy; these studies included 827 cases and 1069 controls [9, 10, 16, 17, 22, 23, 25‐29, 32]. The results showed that there was significant heterogeneity in the dominant model (QR + RR vs QQ: I² = 63.6%, P = 0.001, Fig. 3a, Table 4), homozygous model (RR vs QQ: I² = 64.5%, P = 0.001, Fig. 3b, Table 4), allelic contrast model (R vs Q: I² = 66.5%, P = 0.001, Fig. 3c, Table 4), recessive model (RR vs QQ + QR: I² = 45.7%, P = 0.042, Fig. 3d, Table 4), and heterozygous model (QR vs QQ: I² = 52.5%, P = 0.017, Fig. 3e, Table 4). Subgroup analysis of ethnicity, type of DM, and HWE was therefore conducted, but it failed to find the sources of heterogeneity (Table 4). Meta-regression analysis was then performed using the covariates published year, sample size, ethnicity, type of DM, and HWE. The results showed that sample size could explain the heterogeneity in the dominant allelic and heterozygous models, and HWE could explain the heterogeneity in the homozygous and recessive models (Table 5). Paraoxonase 1 Q192R genetic polymorphism was significantly related to diabetic macroangiopathy susceptibility in the homozygous model (OR 1.88, 95% CI 1.06–3.32, P = 0.030, Fig. 3b, Table 4), allelic contrast model (OR 1.31, 95% CI 1.02–1.69, P = 0.038, Fig. 3c, Table 4), and recessive model (OR 1.55, 95% CI 1.11–2.16, P = 0.010, Fig. 3d, Table 4), but not the dominant model (OR 1.35, 95% CI 0.88–2.08, P = 0.163, Fig. 3a, Table 4) or heterozygous model (OR 1.20, 95% CI 0.81–1.78, P = 0.370, Fig. 3e, Table 4). Sensitivity analysis indicated that when the effects models were changed, the statistical significance did not alter (data not shown). Meanwhile, there was no significant publication bias according to the funnel plot and Egger’s test (QR + RR vs QQ: t = 1.44, P = 0.179; RR vs QQ: t = 1.46, P = 0.174; R vs Q: t = 1.00, P = 0.343; RR vs QQ + QR: t = 1.30, P = 0.224; QR vs QQ: t = 1.03, P = 0.326; data not shown).

As shown in Table 3, twelve studies focused on the association of paraoxonase 1 Q192R genetic polymorphism with the risk of diabetic microangiopathy; these studies included 1455 cases and 1353 controls [8, 10‐12, 14, 17, 19‐21, 24, 25, 30]. The results showed that there was significant heterogeneity in the dominant model (QR + RR vs QQ: I² = 53.5%, P = 0.014, Fig. 4a, Table 4), homozygote model (RR vs QQ: I² = 60.4%, P = 0.004, Fig. 4b, Table 4), and allelic contrast model (R vs Q: I² = 59.3%, P = 0.005, Fig. 4c, Table 4) but not in the recessive model (RR vs QQ + QR: I² = 39.8%, P = 0.075, Fig. 4d, Table 4) and heterozygous model (QR vs QQ: I² = 35.1%, P = 0.109, Fig. 4e, Table 4). Subgroup analysis of ethnicity, type of DM, and HWE and meta-regression analysis using the covariates published year, sample size, ethnicity, type of DM, and HWE were therefore performed to investigate the sources of heterogeneity. Unfortunately, the sources of heterogeneity were not found (Tables 4, 5). There was no marked association between paraoxonase 1 Q192R genetic polymorphism and susceptibility to diabetic microangiopathy in the dominant model (OR 1.21, 95% CI 0.90–1.64, P = 0.209, Fig. 4a, Table 4), the homozygous model (OR 1.33, 95% CI 0.86–2.05, P = 0.119, Fig. 4b, Table 4), the allelic contrast model (OR 1.12, 95% CI 0.93–1.35, P = 0.227, Fig. 4c, Table 4), the recessive model (OR 1.12, 95% CI 0.93–1.33, P = 0.225, Fig. 4d, Table 4), and the heterozygous model (OR 1.12, 95% CI 0.92–1.36, P = 0.272, Fig. 4e, Table 4). Sensitivity analysis indicated that when the effects models were changed, the statistical significances did not alter (data not shown). Meanwhile, according to the funnel plot and Egger’s test, there was no significant publication bias in the models (QR + RR vs QQ: t = 2.19, P = 0.054; RR vs QQ: t = 1.35, P = 0.207; R vs Q: t = 0.69, P = 0.505, RR vs QQ + QR: t = 0.61, P = 0.555; data not shown) except in the heterozygous model (QR vs QQ: t = 2.36, P = 0.040, data not shown).