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Recently, rs163182 in KCNQ1, rs7612463 in UBE2E2, rs7119 in HMG20A, and rs6815464 in MAEA were discovered as type 2 diabetes (T2D) loci unique to Asians, and rs13342692 in SLC16A11 were newly reported as T2D loci in multiethnicities by genome-wide association (GWA) studies. The aim of the present study is to ascertain the potential associations between these variants and T2D risk in the Chinese population, and characterize diabetic-related quantitative traits underlying these variants.
A total of 4268 Chinese Han individuals (1754 patients with T2D and 2514 glucose-tolerant health subjects, age ≥40 years) were genotyped for these 5 variants. All the health individuals underwent an oral glucose tolerance test (OGTT), and measures of insulin release and sensitivity were estimated from insulinogenic, BIGTT, Matsuda, and disposition indices. The associations were determined by using logistic regression analysis.
After adjustment for age, sex, and BMI, rs163182 in KCNQ1 (P=0.002) and rs7612463 in UBE2E2 (P=0.024) were found to be associated with T2D risk in Chinese Han population. The risk C allele of rs7612463 in UBE2E2 is associated with decreased IGI (P=0.001), BIGTT-AIR (P=0.002), CIR (P=0.002), and DI (P=0.006). The other 4 variants did not associate with insulin release or sensitivity.
UBE2E2 rs7612463 may mediate its diabetogenic impact on insulin response, which highly depends on the impairment of β-cell function.
More than 60 genetic loci have been identified with convincing evidence of association with type 2 diabetes (T2D) risk from European large-scale genome-wide association (GWA) studies and meta-analyses, especially reported by the Diabetes Genetics Replication and Meta-analysis (DIAGRAM) Consortium.1 The associations between these loci in European and glucose homeostasis, causal molecular mechanisms on islet function have been well characterized.1,2 Till now, about 20 common T2D risk variants were discovered by Southeast Asian GWA studies,3–10 and most of them were replicated in other studies for their associations with T2D risk and diabetic-related quantitative traits. However, as one of these loci in East Asians,6 rs7612463 in UBE2E2 was reported to be negatively associated with T2D risk in another 2 Japanese case–control studies.11,12 And this variant was investigated for glycemic traits only based on fasting-based homeostasis model assessment of beta cell function (HOMA-β) and insulin resistance (HOMA-IR) indexes.11 Except for rs7612463, rs163182 in KCNQ1,7 rs7119 in HMG20A,9 and rs6815464 in MAEA10 were also reported as independent T2D tag variants, but they have not been extensively replicated in other independent studies, and the results were inconsistent. Furthermore, no glycemic traits about these variants were reported. In addition, rs13342692 in SLC16A11, a novel variant was newly reported in a Mexican GWA study13 and replicated in multiethnicities by the SIGMA Type 2 Diabetes Consortium,14 but its relationship to beta cell function and insulin resistance is still not elucidated.
Therefore, we aimed to evaluate the degree to which these 5 variants confer T2D risk in Chinese Han population. We further performed a meta-analysis on present Chinese study and other eligible Asian case–control studies to provide a quantitative assessment for these variants in Asians, which might have the possibility of reaching reliable and stable conclusions. Due to the sparse knowledge of these variants concerning the diabetes causing mechanisms, and improved precision of the oral glucose tolerance test (OGTT), we subsequently characterized the influence of these variants on surrogate measures of beta cell function and insulin sensitivity derived from an OGTT.
The present work was one part of the baseline survey from REACTION study investigating the association of diabetes and cancer, which was conducted among 259,657 adults, aged 40 years and older in 25 communities across mainland China, from 2011 to 2012.15,16 Diabetes was diagnosed according to the criteria established by the World Health Organization. The exclusion criteria for the subjects with T2D were diabetes caused by liver dysfunction, pancreatitis, gastrointestinal diseases, malignancy, and individuals who tested positive for anti-GAD antibody. The inclusion criteria for the nondiabetic control subjects were as follows: HbA1c ≤6.0% (4.2mmol/mol), fasting plasma glucose<5.6mmol/l and 2hours plasma glucose (postprandial glucose) <7.8mmol/l, no family history of T2D in first-degree relatives, and no past history of a diagnosis of diabetes. Then we enrolled 2514 glucose-tolerant health individuals and 1754 patients with T2D for case–control analyses. Subsequently, 2514 health individuals were further measured for diabetic-related quantitative traits. Clinical characteristics of the study population are shown in the Electronic Supplementary Material (ESM) Table 1. Written informed consent was obtained from all participants prior to investigation. The study was approved by the scientific ethics committee of the First Affiliated Hospital of Nanjing Medical University and conducted in accordance with the principles of the Helsinki Declaration II.
All participants were measured for plasma glucose and serum insulin at fasting, 30 and 120minutes during an OGTT. The insulinogenic index (IGI), BIGTT-acute insulin response (AIR), and the corrected insulin response (CIR) were reported as indices of oral glucose-stimulated insulin release. The surrogate measures of insulin sensitivity were estimated by the Matsuda insulin sensitivity index (ISIMatsuda) and the BIGTT-sensitivity index (SI). The BIGTT indexes integrated information on sex and BMI combined with plasma glucose and serum insulin and were calculated during an OGTT as reported. HOMA-B and HOMA-IR indexes were also calculated for comparison purposes. Beta cell function corrected for insulin sensitivity level was expressed as the disposition index (DI). For DI 1 we multiplied BIGTT-AIR with BIGTT-SI, for DI 2 we divided CIR by HOMA-IR.17 Laboratory measurements and calculation of glycemic traits are provided in ESM Table 2.
Genomic DNA was extracted from peripheral blood (QIAamp DNA blood kit; QIAGEN, Germany). We selected 5 variants at genetic loci that had been reported to be robustly associated with T2D risk in recent GWA studies, including rs163182 in KCNQ1, rs7612463 in UBE2E2, rs7119 in HMG20A, rs6815464 in MAEA, and rs13342692 in SLC16A11. The genotyping of these variants was performed using Sequenom MassArray (BGI CO. LTD, China). Primer sequences and UEP primers used for MassARRAY IPLEX Genotyping are shown in ESM Table 3. The genotyping success call rate was above 97% for all variants, and 215 samples measured in duplicate (≈5%) were in complete concordance. The distributions of genotypes for all variants were in the Hardy–Weinberg equilibrium (all P>0.05). Detailed information is shown in ESM Table 4.
Associations between the investigated 5 variants and T2D risk were tested by an additive model with adjustment for age, sex, and BMI. Correction for multiple testing was performed by the Bonferroni test. P≤0.01 was considered significant, and P value between 0.05 and 0.01 was considered nominally significant. Associations for diabetic-related quantitative traits were examined by the additive model, with adjustment for age (BIGTT indexes and DI 1) or age, sex, and BMI (all other traits). Values of serum insulin, IGI, BIGTT-AIR, CIR, HOMA-B, HOMA-IR, ISIMatsuda, and DI were logarithmically transformed. Correction for multiple testing was performed by the Bonferroni test (correcting for 5 variants). A P value below 0.01 was considered significant, and a P value between 0.05 and 0.01 was considered nominally significant. Statistical analyses were performed using SPSS (version 18.0). Combined meta-analysis was performed using the Mantel–Haenszel procedure with a fixed effect model or the DerSimonian–Laird method with a random effect model after testing for heterogeneity. The genome-wide significance level (P<10−8) was considered significant for meta-analysis. The power of sample size to identify the association of these variants was calculated using the “CaTS power calculator for genetic studies” software (http://www.sph.umich.edu/csg/abecasis/CaTS/). Analyses of statistical power to detect quantitative trait associations were calculated using Quanto software (http://hydra.usc.edu/gxe/).
The genotype distribution of all the 5 investigated variants in the case and control groups did not deviate from HWE (ESM Table 4). The effect directions of these variants were consistent with those reported in previous GWA studies. After adjustment for age, sex, and BMI, rs163182 in KCNQ1 was found to be significantly associated with T2D (odds ratio [OR] 1.165, 95% confidence interval [CI] 1.055, 1.287; P=0.002) and rs7612463 in UBE2E2 showed a nominal association with T2D risk (OR 1.144, 95% CI 1.018, 1.286; P=0.024) (Table (Table1).1). As for rs7119 in HMG20A, rs6815464 in MAEA, and rs13342692 in SLC16A11, we were unable to detect any association with T2D risk in present Chinese samples (P=0.076, 0.565, and 0.515, respectively). When we combined the present data with previous reported Asian studies, the associations of rs163182 and rs7612463 with T2D were further strengthened at the genome-wide significant level (P=1.01×10−16 and 2.01×10−12, respectively). In addition, rs6815464 was also observed to reach a genome-wide significant level with T2D risk (2.45×10−10), but not rs7119 or rs13342692 (ESM Table 5). Moreover, to examine whether these variants also contributed to risk of obesity, the relationship between these variants and log-transformed BMI, overweight/obesity was estimated, but none of them showed any association after adjusted for age and sex, as shown in ESM Tables 6–7.
To identify potential mediators that link these variants with T2D, we analyzed their associations with diabetic-related quantitative traits in 2514 glucose-tolerant health individuals. As shown in Table Table22 and ESM Table 8, after adjustment for age, sex, BMI, carriers of the risk C allele of rs7612463 in UBE2E2 had nominally decreased 30minutes insulin level (P=0.01). For fasting insulin derived indexes (HOMA-IR and HOMA-β), none of the investigated variants exhibited significant difference. Further we estimate insulin release and insulin sensitivity derived from an OGTT. We found that carriers of the risk C allele of rs7612463 had significantly decreased IGI, BIGTT-AIR, and CIR (P=0.001, P=0.002, and P=0.002, respectively), which are consistent with a significant decrease in the estimate of OGTT-based DI (DI2, P=0.006). In addition, our results indicated that carriers of the risk C allele of rs163182 showed a tendency to be associated with decreased IGI, BIGTT-AIR, CIR, and BIGTT-SI (P=0.066, 0.053, 0.071, and 0.079, respectively). But for the remaining 3 variants, our results did not show any convincing association with any diabetic-related quantitative traits (Table (Table22 and ESM Table 8).
As the first T2D variant in East Asian, rs2237892 in KCNQ1 was identified by 3 GWA studies.3,4,18 Recently, rs163182 was reported as another independent T2D tag variant in KCNQ1 by a Chinese GWA study.7 Our case–control study and meta-analysis confirmed that rs163182 was significantly associated with T2D in Asians. Although studies indicated that other intronic T2D variants in KCNQ1, such as rs2237892, rs2237895, and rs2237897,19,20 were associated with impaired β-cell function, our study did not support any association between rs163182 and diabetic-related quantitative traits. Interestingly, contradictory results were reported on the relationship between variants in KCNQ1 and metabolic traits, including rs2237892, rs2237895, and rs2237897. A study from Liu et al21 revealed that homozygous carriers of these 3 variants had significantly decreased BMI and waist circumferences in control individuals, another study from Yu et al showed that they were associated with lower BMI and lower incidence of overweight/obesity only in diabetic patients, but not in controls.22 But for rs163182 in KCNQ1, we did not find any association with either BMI or overweight/obesity in present study. This implies that rs163182 might not be an obesity risk variant.
Following the identification of KCNQ1, rs7612463 in UBE2E2 was subsequently reported as another Asian T2D risk variant in a Japanese GWA study.6 Although 2 replicated Japanese case–control studies reported that this variant was negatively associated with T2D risk, our case–control study and further meta-analysis confirmed an association of this variant and T2D at the genome-wide significant level in Asians. Interestingly, DIAGRAM study did not detect any association between this variant and T2D in Europeans, instead they identified that rs1496653 in UBE2E2 were the strongest causal T2D variants for Europeans.1 This implicated that examining population-specific causal variants may provide insights into the functional biology that may differ among different ethnic groups. Actually, UBE2E2 is expressed in both human pancreas and a cultured insulin-secreting cell line, and encodes the ubiquitin-conjugating enzyme E2E2, which has been known to play a pivotal role in maintaining normal insulin biosynthesis, secretion, and signaling in pancreatic β cells.23,24 Assessed by fasting-based homeostasis model, recently studies indicated that rs7612463 was not associated with HOMA-β or HOMA-IR,11,25 which was confirmed by our results. However, when further applying OGTT-derived indexes, we found that rs7612463 did have a significant association with insulin release indices, including IGI, BIGTT-AIR, and CIR. As different indexes may capture different mechanisms of insulin release, our results implicated that the C risk allele of rs7612463 in UBE2E2 might impair β-cell function by decreasing glucose-stimulated insulin response, which was confirmed by a significant decrease in 30minutes insulin levels after applying OGTT. Furthermore, the concomitant decrease in DI suggested that, even if insulin-responsive tissues were affected by the variant, the β-cell defect may be the most profound.
As for the other 2 reported Asian T2D risk variants, rs7119 in HMG20A and rs6815464 in MAEA9,10 did not associate with T2D in present Chinese population. Although we had sufficient power (>80% for α=0.05) to estimate the association reported previously, it cannot be completely ruled out that differences in study design and/or experimental procedures may underlie the discrepancy between studies. When we further combined our data with previously reported studies, we found that the association between rs6815464 and T2D risk in Asian populations reached a genome-wide significance level, but not rs7119. Furthermore, we did not find any association between rs7119 and T2D when stratified to obesity, although a study from South Asians identified that rs7178572, another variant in HMG20A, was significantly associated with T2D in obese cases (P=1.3×10−8, OR=1.11, 95%CI 1.07–1.15).26 In addition, similar to rs7177055,27 another variant in HMG20A, rs7119 associated neither insulin release nor insulin resistance in our present study. For rs6815464 in MAEA, we did not find any association with the OGTT-derived traits either. Till now, the function of HMG20A and MAEA is still not clear, further functional characterization is required to elucidate their role in the pathogenesis of T2D.
No association between rs13342692 in SLC16A11 and T2D risk or diabetic-related quantitative traits was found in our present study despite the fact that this newly discovered variant was found in Mexican and multiethnic cohorts.14 However, as a missense variant (D127G), rs13342692 was labeled as damaging by computational prediction with SIFT28 and thus, conclusions based on this variant alone should be interpreted with caution. Actually, SLC16A11 is expressed in liver and acts as a regulator of lipid metabolism, most notably causing an increase in intracellular triacylglycerol levels.13 But its role in the pathogenesis of T2D is still unknown and needs further studies.
We also performed statistical power analyses for the investigated variants in different scenarios (ESM Table 9), demonstrating the need for combining efforts in further meta-analyses when searching for the diabetes intermediary phenotype. Only ~5% to 20% of heritability for most common diseases has been explained, when provided a limited glimpse into the full architecture of a given trait.29 In this regard, further studies should be proposed to explain missing heritability, such as the identification of rare or low-frequency variants, copy number variations, gene–gene interaction, and gene–environment interaction, etc.
In conclusion, our study suggested that rs163182 in KCNQ1, rs7612463 in UBE2E2, and rs6815464 in MAEA are associated with T2D risk in Asians, and risk alleles of rs7612463 in UBE2E2 might be associated with an impairment of beta cell function.
The authors thank the National Natural Science Foundation of China (numbers 30971405 and 81270897), the Natural Science Foundation of Jiangsu province (number BK2012486), Jiangsu Government Scholarship for Overseas Studies (JS-2013-260), the Chinese Society of Endocrinology and National Clinical Research Center for Metabolic Diseases, and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) for the support. The authors also thank Dr Eddie James and Dr S Alice Long at Benaroya Research Institute at Virginia Mason, Seattle, WA, US for both their revision of the manuscript.
Abbreviations: AIR = acute insulin response, CI = confidence interval, CIR = corrected insulin response, DI = disposition index, GWA = genome-wide association, IGI = insulinogenic index, OGTT = oral glucose tolerance test, OR = odds ratio, T2D = type 2 diabetes.
KX, LJ, MS, and XZ contributed equally to this work.
KX: conception and design, analysis and interpretation of data, drafting of the manuscript; ZW, MS, XZ, HD, YS, SZ, YC, and LJ: collection and selection of samples; JL, YG, YC, XX, HC, and MZ: analysis and interpretation of data; TY: conception and design, and critical revision of the manuscript; and all the co-authors gave final approval of the version to be published.
Duality of interest: The authors declare that there is no duality of interest associated with this manuscript.
This study was supported by grants from the National Natural Science Foundation of China (numbers 30971405 and 81270897), the Natural Science Foundation of Jiangsu province (number BK2012486), Jiangsu Government Scholarship for Overseas Studies (JS-2013-260), the Chinese Society of Endocrinology and National Clinical Research Center for Metabolic Diseases, and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).
The authors have no conflicts of interest to disclose.
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