Lee YH, etal., J Hum Genet. 2008;53(11-12):991-8. Epub 2008 Nov 11.
According to recent genome-wide association studies, a number of single nucleotide polymorphisms (SNPs) are reported to be associated with type 2 diabetes mellitus (T2DM). The aim of the present study was to investigate the association among the polymorphisms of SLC30A8, HHEX, CDKN2A/B, IGF2BP2
'font-weight:700;'>IGF2BP2, FTO, WFS1, CDKAL1 and KCNQ1 and the risk of T2DM in the Korean population. This study was based on a multicenter case-control study, including 908 patients with T2DM and 502 non-diabetic controls. We genotyped rs13266634, rs1111875, rs10811661, rs4402960, rs8050136, rs734312, rs7754840 and rs2237892 and measured the body weight, body mass index and fasting plasma glucose in all patients and controls. The strongest association was found in a variant of CDKAL1 [rs7754840, odds ratio (OR) = 1.77, 95% CI = 1.50-2.10, p = 5.0 x 10(-11)]. The G allele of rs1111875 (OR = 1.43, 95% CI = 1.18-1.72, p = 1.8 x 10(-4)) in HHEX), the T allele of rs10811661 (OR = 1.47, 95% CI = 1.23-1.75, p = 2.1 x 10(-5)) in CDKN2A/B) and the C allele of rs2237892 (OR = 1.31, 95% CI = 1.10-1.56, p = 0.003) in KCNQ1 showed significant associations with T2DM. Rs13266634 (OR = 1.19, 95% CI = 1.00-1.42, p = 0.045) in SLC30A8 showed a nominal association with the risk of T2DM, whereas SNPs in IGF2BP2, FTO and WFS1 were not associated. In conclusion, we have shown that SNPs in HHEX, CDKN2A/B, CDKAL1, KCNQ1 and SLC30A8 confer a risk of T2DM in the Korean population.
Wu Y, etal., Diabetes. 2008 Oct;57(10):2834-42. Epub 2008 Jul 15.
OBJECTIVE: Genome-wide association studies have identified common variants in CDKAL1, CDKN2A/B, IGF2BP2, SLC30A8, HHEX/IDE, EXT2, and LOC387761 loci that significantly increase the risk of type 2 diabetes. We aimed to replicate these observations in a population
-based cohort of Chinese Hans and examine the associations of these variants with type 2 diabetes and diabetes-related phenotypes. RESEARCH DESIGN AND METHODS: We genotyped 17 single nucleotide polymorhisms (SNPs) in 3,210 unrelated Chinese Hans, including 424 participants with type 2 diabetes, 878 with impaired fasting glucose (IFG), and 1,908 with normal fasting glucose. RESULTS: We confirmed the associations between type 2 diabetes and variants near CDKAL1 (odds ratio 1.49 [95% CI 1.27-1.75]; P = 8.91 x 10(-7)) and CDKN2A/B (1.31 [1.12-1.54]; P = 1.0 x 10(-3)). We observed significant association of SNPs in IGF2BP2 (1.17 [1.03-1.32]; P = 0.014) and SLC30A8 (1.12 [1.01-1.25]; P = 0.033) with combined IFG/type 2 diabetes. The SNPs in CDKAL1, IGF2BP2, and SLC30A8 were also associated with impaired beta-cell function estimated by homeostasis model assessment of beta-cell function. When combined, each additional risk allele from CDKAL1-rs9465871, CDKN2A/B-rs10811661, IGF2BP2-rs4402960, and SLC30A8-rs13266634 increased the risk for type 2 diabetes by 1.24-fold (P = 2.85 x 10(-7)) or for combined IFG/type 2 diabetes by 1.21-fold (P = 6.31 x 10(-11)). None of the SNPs in EXT2 or LOC387761 exhibited significant association with type 2 diabetes or IFG. Significant association was observed between the HHEX/IDE SNPs and type 2 diabetes in individuals from Shanghai only (P < 0.013) but not in those from Beijing (P > 0.33). CONCLUSIONS: Our results indicate that in Chinese Hans, common variants in CDKAL1, CDKN2A/B, IGF2BP2, and SLC30A8 loci independently or additively contribute to type 2 diabetes risk, likely mediated through beta-cell dysfunction.
Liu X, etal., Pharmacogenomics. 2015;16(9):959-70. doi: 10.2217/pgs.15.49. Epub 2015 Jun 26.
AIM: The present study analyzed Type 2 diabetes mellitus (T2D)-related gene polymorphisms and their impacts on chemotherapeutic response and survival in patients with metastatic gastric cancer (MGC). PATIENTS & METHODS: This retrospective study enrolled 108 MGC patients treated with first-line EOF c
hemotherapy (epirubicin, oxaliplatin and 5-fluorouracil combination chemotherapy). Eleven single nucleotide polymorphisms of five T2D-related genes were determined. RESULTS: Among the 11 single nucleotide polymorphisms, three (IGF2BP2 rs4402960, IGF2BP2 rs6769511 and KCNQ1 rs163182) were significantly associated with disease control rate and two (GCKR rs780093 and rs780094) were significantly associated with progression-free and overall survival. CONCLUSION: Our results suggest IGF2BP2 and KCNQ1 polymorphisms might be independent predictors of chemotherapeutic response, while GCKR polymorphisms might be independent predictors of survival in MGC patients treated with first-line EOF chemotherapy. Original submitted 30 June 2014; revision submitted 15 April 2015.
Wang MH, etal., Meta Gene. 2014 May 21;2:384-91. doi: 10.1016/j.mgene.2014.04.010. eCollection 2014 Dec.
Metabolic disorders including type 2 diabetes, obesity and hypertension have growing prevalence globally every year. Genome-wide association studies have successfully identified many genetic markers associated to these diseases, but few studied their interaction effects. In this study, twenty candid
ate SNPs from sixteen genes are selected, and a lasso-multiple regression approach is implemented to consider the SNP-SNP interactions among them in an Asian population. It is found out that the main effects of the markers are weak but the interactions among the candidates showed a significant association to diseases. SNPs from genes CDKN2BAS and KCNJ11 are significantly associated to risk for developing diabetes, and SNPs from FTO and APOA5 might interact to play an important role for the onset of hypertension.
Sanghera DK, etal., BMC Med Genet. 2008 Jul 3;9:59.
BACKGROUND: Recent genome-wide association (GWA) studies have identified several unsuspected genes associated with type 2 diabetes (T2D) with previously unknown functions. In this investigation, we have examined the role of 9 most significant SNPs reported in GWA studies: [peroxisome proliferator-ac
tivated receptor gamma 2 (PPARG2; rs 1801282); insulin-like growth factor two binding protein 2 (IGF2BP2; rs 4402960); cyclin-dependent kinase 5, a regulatory subunit-associated protein1-like 1 (CDK5; rs7754840); a zinc transporter and member of solute carrier family 30 (SLC30A8; rs13266634); a variant found near cyclin-dependent kinase inhibitor 2A (CDKN2A; rs10811661); hematopoietically expressed homeobox (HHEX; rs 1111875); transcription factor-7-like 2 (TCF7L2; rs 10885409); potassium inwardly rectifying channel subfamily J member 11(KCNJ11; rs 5219); and fat mass obesity-associated gene (FTO; rs 9939609)]. METHODS: We genotyped these SNPs in a case-control sample of 918 individuals consisting of 532 T2D cases and 386 normal glucose tolerant (NGT) subjects of an Asian Sikh community from North India. We tested the association between T2D and each SNP using unconditional logistic regression before and after adjusting for age, gender, and other covariates. We also examined the impact of these variants on body mass index (BMI), waist to hip ratio (WHR), fasting insulin, and glucose and lipid levels using multiple linear regression analysis. RESULTS: Four of the nine SNPs revealed a significant association with T2D; PPARG2 (Pro12Ala) [odds ratio (OR) 0.12; 95% confidence interval (CI) (0.03-0.52); p = 0.005], IGF2BP2 [OR 1.37; 95% CI (1.04-1.82); p = 0.027], TCF7L2 [OR 1.64; 95% CI (1.20-2.24); p = 0.001] and FTO [OR 1.46; 95% CI (1.11-1.93); p = 0.007] after adjusting for age, sex and BMI. Multiple linear regression analysis revealed significant association of two of nine investigated loci with diabetes-related quantitative traits. The 'C' (risk) allele of CDK5 (rs 7754840) was significantly associated with decreased HDL-cholesterol levels in both NGT (p = 0.005) and combined (NGT and T2D) (0.005) groups. The less common 'C' (risk) allele of TCF7L2 (rs 10885409) was associated with increased LDL-cholesterol (p = 0.010) in NGT and total and LDL-cholesterol levels (p = 0.008; p = 0.003, respectively) in combined cohort. CONCLUSION: To our knowledge, this is first study reporting the role of some recently emerged loci with T2D in a high risk population of Asian Indian origin. Further investigations are warranted to understand the pathway-based functional implications of these important loci in T2D pathophysiology in different ethnicities.
BACKGROUND: Recent advance in genetic studies added the confirmed susceptible loci for type 2 diabetes to eighteen. In this study, we attempt to analyze the independent and joint effect of variants from these loci on type 2 diabetes and clinical phenotypes related to glucose metabolism. METHODS/PRIN
CIPAL FINDINGS: Twenty-one single nucleotide polymorphisms (SNPs) from fourteen loci were successfully genotyped in 1,849 subjects with type 2 diabetes and 1,785 subjects with normal glucose regulation. We analyzed the allele and genotype distribution between the cases and controls of these SNPs as well as the joint effects of the susceptible loci on type 2 diabetes risk. The associations between SNPs and type 2 diabetes were examined by logistic regression. The associations between SNPs and quantitative traits were examined by linear regression. The discriminative accuracy of the prediction models was assessed by area under the receiver operating characteristic curves. We confirmed the effects of SNPs from PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX, IGF2BP2 and SLC30A8 on risk for type 2 diabetes, with odds ratios ranging from 1.114 to 1.406 (P value range from 0.0335 to 1.37E-12). But no significant association was detected between SNPs from WFS1, FTO, JAZF1, TSPAN8-LGR5, THADA, ADAMTS9, NOTCH2-ADAM30 and type 2 diabetes. Analyses on the quantitative traits in the control subjects showed that THADA SNP rs7578597 was association with 2-h insulin during oral glucose tolerance tests (P = 0.0005, empirical P = 0.0090). The joint effect analysis of SNPs from eleven loci showed the individual carrying more risk alleles had a significantly higher risk for type 2 diabetes. And the type 2 diabetes patients with more risk allele tended to have earlier diagnostic ages (P = 0.0006). CONCLUSIONS/SIGNIFICANCE: The current study confirmed the association between PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX, IGF2BP2 and SLC30A8 and type 2 diabetes. These type 2 diabetes risk loci contributed to the disease additively.
