Combined Effect Of Single Nucleotide Polymorphisms Research Articles

Association Between Selected Single Nucleotide Polymorphisms in Globin and Related Genes and Response to Hydroxyurea Therapy in Ghanaian Children with Sickle Cell Disease.

BackgroundSickle cell disease (SCD) is a group of genetic disorders affecting the structure and function of haemoglobin. Hydroxyurea (HU) stimulates fetal haemoglobin (HbF) and reduces sickle erythrocyte-endothelial cell interaction. However, the degree of HbF response to HU varies, with HbF expression-associated single nucleotide polymorphisms (SNPs) in quantitative trait loci (QTL) been implicated. We investigated the relationship between four SNPs (rs11886868, rs6706648, rs7606173 and 158C/T Xmn1) in two QTL (B-cell lymphoma 11A (BCL11A) and Xmn1) and HbF levels in children with SCD in Accra, Ghana.MethodsA total of 110 children with SCD in steady-state, comprising 64 and 46 SCD children treated with HU (HU+) or with no history of HU therapy (HU-), respectively, were recruited. HbF levels were measured in peripheral blood by alkali denaturation and SNPs were genotyped using polymerase chain reaction and restriction fragment length polymorphism.ResultsThe presence of SNPs (rs11886868, rs6706648, rs7606173 and −158C/T Xmn1) was identified. Observed heterozygosity and homozygosity for the derived alleles were 45.7%, 82.6%, 21.7% and 39.1% in rs11886868, rs6706648, rs7606173 and −158C/T Xmn1 polymorphisms, respectively, for the HU+ population. Observed frequencies of the minor alleles were 0.204, 0.477, 0.171 and 0.190 for rs11886868, rs6706648, rs7606173 and −158C/T Xmn1 polymorphisms, respectively. The three BCL11A SNPs in the HU+ population showed homozygous individuals for rs11886868 (CC), rs6706648 (CC) and heterozygous or homozygous mutant individuals for rs7606173 (CG/GG) having higher HbF values. The combined effect of the SNPs was associated with variance in HbF levels in the HU+ population. The BCL11A SNP, rs6706648 was strongly associated with HbF levels and the C allele frequency, with significantly elevated HbF levels.ConclusionAn association between the various variants and combined effect of SNPs and HbF among children with SCD was found and confirms the known association between HU intake and increased HbF in SCD.

Intercellular Adhesion Molecule-1 Gene Polymorphisms and Susceptibility to Cervical Cancer in the Northern Chinese Han Population.

Many epidemiological studies have confirmed that ICAM-1 gene single-nucleotide polymorphisms (SNPs) are associated with susceptibility of various cancers, but there are relatively few studies on the relationship between ICAM-1 gene polymorphisms and the risk of cervical cancer. Therefore, we aimed to explore the potential role of ICAM-1 gene polymorphisms and the combined effect of SNPs in the pathogenesis of cervical cancer in Han women in northern China. This case–control group includes 488 cases of cervical cancer, 684 cases of cervical precancerous lesions, and 510 healthy females. Multiplex polymerase chain reaction (PCR) combined with the next-generation sequencing method was used for the determination of gene polymorphisms (rs5498, rs3093030, and rs281432). In our study, we divide cervical cancer into two subgroups: cervical squamous cell carcinoma (CSCC) group and cervical adenocarcinoma (CAC) group. We analyzed the alleles and genotypes of all research subjects using multivariate logistic regression analysis combined with 10,000 permutation tests. In addition, we also analyzed the distribution of haplotypes of the three SNPs in cervical cancer and cervical precancerous lesions. We found that the T allele and the dominant model of rs3093030 were associated with the susceptibility of cervical cancer (p = 0.042, p = 0.040, respectively). However, the significance disappeared after the Bonferroni correction for multiple testing (p > 0.05). For rs5498, its mutant gene G, the codominant model, and the dominant model could reduce the risk of CAC (p = 0.009, p = 0.028, p = 0.011, respectively). Significant differences remained after Bonferroni correction (p < 0.05, all). In addition, the frequency of haplotype “CTG” was significantly lower in the CAC group than in the controls. In conclusion, the study suggested that ICAM-1 gene polymorphisms may have a potential role in the pathogenesis of cervical cancer in the northern Chinese Han population.

An Exploration of ABCG2 and SLC2A9 Gene Interactions with Gout

Background: Currently, there is no systematic analysis of single nucleotide polymorphisms (SNPs) in the urate transporter genes (ABCG2 and SLC2A9), and the influence of their combination and gene-gene (G×G) interactions on gout is still unknown in the Thai population. Objective: To investigate the interaction between ABCG2 and SLC2A9 with gout. Materials and Methods: A matched case-control study with 116 Thai adults (58 gout patients and 58 control subjects) was done. Genotyping using a TaqMan SNP Genotyping Assays was performed. G×G interactions for gout risk were analyzed using an interaction analysis in multiple conditional logistic regression. Results: The results show that the rs2231142 (G/T+T/T) variants in ABCG2 was associated with gout. On the contrary, the rs2280205 (G/A+A/A) and rs6820230 (C/T–T/T) variant in SLC2A9 were not associated with gout. The result indicated that the participants carrying ABCG2 variant with SLC2A9 wild-type (i.e., original base pairs) had a significant association with gout. The present study results also revealed that epistatic interaction pairs (rs2231142:rs6820230 and rs2231142:rs2280205) were strongly associated with gout. Conclusion: The authors concluded that the ABCG2 and SLC2A9 interactions were a significant association with gout. The stronger combined effect of SNPs in the ABCG2 and SLC2A9 genes via G×G interaction may help to predict gout risk and its prognosis. However, further studies with larger sample sizes should be performed to confirm these results. Keywords: Gene-gene interactions, Gout, ABCG2 gene, SLC2A9 gene

Association of genetic variants in lncRNA GAS5/miR-21/mTOR axis with risk and prognosis of coronary artery disease among a Chinese population.

BackgroundAllowing for the significance of single nucleotide polymorphisms (SNPs) in reflecting disease risk, this investigation attempted to uncover whether SNPs situated in lncRNA GAS5/miR‐21/mTOR axis were associated with risk and prognosis of coronary heart disease (CHD) among a Chinese Han population.MethodsAltogether 436 patients with CHD were recruited as cases, and meanwhile, 471 healthy volunteers were included into the control group. Besides, SNPs of GAS5/MIR‐21/mTOR axis were genotyped utilizing mass spectrometry. Chi‐square test was applied to figure out SNPs that were strongly associated with CHD risk and prognosis, and combined effects of SNPs and environmental parameters on CHD risk were evaluated through multifactor dimensionality reduction (MDR) model.ResultsSingle nucleotide polymorphisms of GAS5 (ie, rs2067079 and rs6790), MIR‐21 (ie, rs1292037), and mTOR (rs2295080, rs2536, and rs1034528) were associated with susceptibility to CHD, and also Gensini score change of patients with CHD (P < .05). MDR results further demonstrated that rs2067079 and rs2536 were strongly interactive in elevating CHD risk (P < .05), while smoking, rs6790 and rs2295080 showed powerful reciprocity in predicting Gensini score change of patients with CHD (P < .05).ConclusionSingle nucleotide polymorphisms of lncRNA GAS5/miR‐21/mTOR axis might interact with smoking to regulate CHD risk, which was conducive to diagnosis and prognostic anticipation of CHD.

Combined Effects of Single Nucleotide Polymorphisms (SNPs) within C-reactive Protein (CRP) and Environmental Parameters on Risk and Prognosis for Diabetic Foot Osteomyelitis Patients.

This study was aimed to discover the combined effects of single nucleotide polymorphisms (SNPs) within the C-reactive protein (CRP) gene and potential environmental factors on the risk and prognosis for diabetic foot osteomyelitis (DFO). A total of 1734 diabetes mellitus patients, 681 with DFO and 1053 without DFO, were successfully recruited, as well as 1261 healthy control individuals. Participants data were recorded regarding age, gender, smoking and drinking history, body mass index (BMI), hypertension, cacosmia, and ulceration. A total of 11 SNPs within the CRP gene were designated for exploration, by logistic regression analyses, of how they might interact with environmental factors to affect susceptibility to DFO. Frequencies of smoking and drinking, and incidence of hypertension, cacosmia, or ulceration displayed marked differences (all P<0.05) between DFO and non-DFO patients. Furthermore, allele G of rs11265260 (A>G), allele G of rs1800947 (C>G), and allele T of rs3093059 (T>C) and rs1130864 (C>T) exhibited a trend to increase risk of DFO (all P<0.05). Allele G of rs11265260 (A>G), allele G of rs1800947 (C>G) and rs3093068 (G>C), and allele T of rs1130864 (C>T) were significant predictors of poor prognosis among DFO patients (P<0.05). In addition, genotypes of rs11265260 (i.e., GG and AG), rs1800947 (i.e., CG and GG), rs3093059 (i.e., TT) and rs113084 (i.e., CT and TT) amplified the influence of smoking, alcohol consumption, cacosmia, and ulceration on progression from non-DFO to DFO (all γ>1). Genetic mutations within CRP functioned interactively with external factors to affect DFO risk.

Abstract 1596: Genome-wide gene-environmental interaction and random survival forest analyses: Insulin resistance and breast cancer risk

Abstract Purpose: Obesity–insulin connections have been considered potential risk factors for postmenopausal breast cancer, and the association between insulin resistance (IR) genotypes and phenotypes can be modified by obesity-lifestyle factors, affecting breast cancer risk. We explored the role of IR in those pathways at the genome-wide level. With identified IR genetic factors and selected lifestyles, we further generated risk profiles for breast cancer risk. Methods: Using large-scale cohort data from postmenopausal women in the Women’s Health Initiative Database for Genotypes and Phenotypes Study, our previous genome-wide association gene–behavior interaction study identified 58 loci for associations with IR phenotypes (homeostatic model assessment–IR, hyperglycemia, and hyperinsulinemia). We evaluated those single-nucleotide polymorphisms (SNPs) and additional 31 lifestyles in relation to breast cancer risk by conducting a two-stage multimodal random survival forest analysis. Results: We identified the most predictive genetic and lifestyle variables in overall and subgroup analyses (stratified by body mass index [BMI], exercise, and dietary fat intake). Two SNPs (LINC00460 rs17254590 and MKLN1 rs117911989), endogenous and exogenous factors related to lifetime cumulative exposure to estrogen, BMI, and dietary alcohol intake were the most common influential factors across the analyses. Individual SNPs did not have significant associations with breast cancer, but the combined SNPs and lifestyles synergistically increased the risk of breast cancer in a dose-dependent manner. In subgroup analysis, we further stratified women by the two strongest variables (durations of oral contraceptive [OC] and opposed estrogen use). Shorter-duration OC and ever-opposed estrogen users with both risks of genotypes and lifestyles had greater risk (2.5 times and 6.3 times, respectively) than their counterparts without risks in both. This indicates the combined effect of SNPs and lifestyles and the joint effect with OC use and opposed estrogen on breast cancer risk. Conclusions: Our findings may contribute to more accurate prediction of breast cancer and suggest intervention strategies for those women with genetic risk to reduce their breast cancer risk. Citation Format: Su Yon Jung, Herbert Yu, Matteo Pellegrini, Jeanette Papp, Eric Sobel, Zuo-Feng Zhang. Genome-wide gene-environmental interaction and random survival forest analyses: Insulin resistance and breast cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1596.

Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks

Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous pathway-based methods have been developed. Here we propose a novel method, DGAT-path, to divide all SNPs assigned to genes in each pathway into LD blocks, and to sum the chi-square statistics of LD blocks for assessing the significance of the pathway by permutation tests. The method was proven robust with the type I error rate >1.6 times lower than other methods. Meanwhile, the method displays a higher power and is not biased by the pathway size. The applications to the GWAS summary statistics for schizophrenia and breast cancer indicate that the detected top pathways contain more genes close to associated SNPs than other methods. As a result, the method identified 17 and 12 significant pathways containing 20 and 21 novel associated genes, respectively for two diseases. The method is available online by http://sparks-lab.org/server/DGAT-path.

Abstract B19: A clinical evaluation of the clinical utility of genotype risk scores in cancer health disparities

Abstract Background: Substantial uncertainty exists as to whether combining multiple disease-associated single nucleotide polymorphisms (SNPs) into a genotype risk score (GRS) can provide clinically useful information. Methods: We critically evaluated the ability of a simple count GRS to predict the risk of a dichotomous outcome, under both a multiplicative (log additive) and linear additive model of combined effects. We also evaluated the ability of a count GRS to predict the level of a continuous outcome variable. We then compared the results of these simulations with the observed results of published GRS measured within multiple epidemiologic cohort studies on cancer health disparities. Results: If the combined effect of each disease-associated SNP included in a GRS is multiplicative on the risk scale, then a count GRS score should be useful for risk stratification with as few as 10-20 SNPs. Adding additional SNPs to the GRS under this model dramatically improves risk stratification with modest gains in risk discrimination. By contrast, if the combined effect of each SNP included in a GRS is linearly additive on the risk scale, a simple count GRS is unlikely to provide clinically useful risk prediction or discrimination. Adding additional SNPs to the GRS under this model does not improve any measures of clinical utility. The combined effect of SNPs included in a GRS measured in several epidemiologic cohort studies appears to be more consistent with a linearly additive combined effect. Unlike the case for predicting a dichotomous outcome, a simple count GRS can potentially provide clinically useful information to predict the level of a continuous outcome variable under a wide variety of circumstances, even when the amount of explained variance is low. Conclusion: A simple count GRS can provide clinically useful information to predict the level of a continuous variable under a variety of circumstances. By contrast, a count GRS is unlikely to be clinically useful for predicting the risk of a dichotomous outcome. To provide clinically useful information about the genetic risk of dichotomous outcomes, alternative methods for constructing GRS that attempt to identify and include SNPs whose combined effect is at least multiplicative are needed. Citation Format: Wonsuk Yoo. A clinical evaluation of the clinical utility of genotype risk scores in cancer health disparities. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr B19. doi:10.1158/1538-7755.DISP13-B19

Combined effects of six cytokine gene polymorphisms and SNP-SNP interactions on hepatocellular carcinoma risk in Southern Guangxi, China.

Cytokine gene single nucleotide polymorphisms (SNPs) are involved in the genesis and progression of hepatocellular carcinoma (HCC). We hypothesized that combined effects of cytokine gene SNPs and SNP-SNP interactions are associated with HCC risk. Six SNPs in cytokine genes (IL-2, IFN-γ, IL-1β, IL-6, and IL-10) were genotyped in a study of 720 Chinese HCC cases and 784 cancer-free controls. Although none of these SNPs individually had a significant effect on the risk of HCC, we found that the combined effects of these six SNPs may contribute to HCC risk (OR=1.821, 95% CI=1.078-3.075). This risk was pronounced among smokers, drinkers, and hepatitis B virus carriers. A SNP-SNP interaction between IL-2-330 and IFN-γ-1615 was associated with an increased HCC risk (OR=1.078, 95% CI=1.022-1.136). In conclusion, combined effects of SNPs and SNP-SNP interactions in cytokine genes may contribute to HCC risk.

Interferon-λ Genetic Variations and Hepatitis C: Yet to be Discovered.

Dear Editor, The association of genetic factors with treatment induced hepatitis C clearance in Pakistani patients was recently demonstrated by Tipu et al. (1). They evaluated the impact of different genetic variants in interferon-λ (IFNL) genomic region on treatment induced hepatitis C clearance. The study was remarkable regarding the investigation of several numbers of single nucleotide polymorphisms (SNPs) in IFNL region. We would like to express our comments regarding the study. We observed that the patients in the study were treated with interferon (IFN) alpha 2b and ribavirin (RBV). Since the combination of pegylated IFN and RBV has been approved for treatment of chronic hepatitis C from 2002, the conventional regimen (IFN alpha 2b and RBV) for treatment of hepatitis C virus (HCV) infected patients is a debate point. Also, we have a concern regarding two terms through the article, first the authors defined the term sustained virologic response (SVR) as undetectable HCV RNA at the end of treatment course, whereas SVR must be defined as undetectable HCV RNA 24 weeks after treatment completion; second the term spontaneous clearance which refers to clearance of HCV from serum without treatment was misused through the article. Interestingly, the current study showed significant association between different IFNL polymorphisms and treatment response in HCV genotype 3 infected patients in our neighbor country (Pakistan). The results of previous studies searching for the association of IL28B SNPs and SVR in patients infected with HCV genotype 2/3 were conflicting and most of them did not find any association between IL28B SNPs and SVR (2, 3). Also, in this study, 50 SNPs were genotyped of which 25 of them were included in the final association analysis and 13 of them were found to be associated with the treatment response (1). The role of SNPs in the IFNL region remained mysterious and yet to be discovered. There are two main hypotheses for the role of these SNPs: Combined effect of SNPs which refers to independent impact of each SNP; Causal and Tag SNPs which is defined by the linkage disequilibrium (LD) between few tag SNPs and a causal SNP (sometimes undiscovered or untested). Most of the SNPs in IFNL region including the SNPs found by Tipu et al. (1) to be associated with treatment response are in linkage disequilibrium (LD) which favors the Causal and Tag SNPs hypothesis. On the other hand, Prokunina-Olsson et al. (4) discovered a new IFNL gene which was assigned as IFNL4 and its encoded protein was observed to possess antiviral activity. Also, in the latter study, a genetic variant called ss469415590 (TT/ΔG) found to be located in exon one of IFNL4 gene which its TT allele does not express the protein and was associated with favorable treatment outcome and its ΔG allele expresses the IFNL4 protein and was associated with treatment nonresponse. The results of most previous studies looked for the functional role of IFNL SNPs showed the pretreatment expression of interferon stimulated genes (ISG) to be lower in patients with SVR when compared to patients with treatment failure. The same finding was observed for the expression of ISGs and IL28B genotypes in which the expression of ISGs were lower in patients with IFNL favorable genotypes than in patients with IFNL unfavorable genotypes (5, 6). However, the results of studies investigated the association of IL28B genotypes with IL28B expression were inconsistent which makes it difficult to draw the final role map (5-9). Discovery of IFNL4 gene and the exon one TT/ΔG SNP was a clue for solving the puzzle of IFNL genetic variations and HCV treatment response. If we accept the ss469415590 as the casual variant, the association of the IFNL genetic variants, IFNL4 expression, the subsequent ISGs expression, and the ultimate differences in treatment response seems to be relevant. In conclusion, studies such the one by Tipu et al. can open new horizons in diagnosis, management, and evaluation of hepatitis C prognosis in near future.

Toll-like receptor-associated sequence variants and prostate cancer risk among men of African descent

BACKGROUNDRecent advances demonstrate a relationship between chronic/recurrent inflammation and prostate cancer (PCA). Among inflammatory regulators, toll-like receptors (TLRs) play a critical role in innate immune responses. However, it remains unclear whether variant TLR genes influence PCA risk among men of African descent. Therefore, we evaluated the impact of 32 TLR-associated single nucleotide polymorphisms (SNPs) on PCA risk among African-Americans and Jamaicans.METHODSSNP profiles of 814 subjects were evaluated using Illumina’s Veracode genotyping platform. Single and combined effects of SNPs in relation to PCA risk were assessed using age-adjusted logistic regression and entropy-based multifactor dimensionality reduction (MDR) models.RESULTSSeven sequence variants detected in TLR6, TOLLIP, IRAK4, IRF3 were marginally related to PCA. However, none of these effects remained significant after adjusting for multiple hypothesis testing. Nevertheless, MDR modeling revealed a complex interaction between IRAK4 rs4251545 and TLR2 rs1898830 as a significant predictor of PCA risk among U.S. men (permutation testing p-value = 0.001).CONCLUSIONSMDR identified an interaction between IRAK4 and TLR2 as the best two factor model for predicting PCA risk among men of African descent. However, these findings require further assessment and validation.

Accurate Single-Nucleotide Polymorphism Allele Assignment in Trisomic or Duplicated Regions by Using a Single Base–Extension Assay with MALDI-TOF Mass Spectrometry

The accurate assignment of alleles embedded within trisomic or duplicated regions is an essential prerequisite for assessing the combined effects of single-nucleotide polymorphisms (SNPs) and genomic copy number. Such an integrated analysis is challenging because heterozygotes for such a SNP may be one of 2 genotypes-AAB or ABB. Established methods for SNP genotyping, however, can have difficulty discriminating between the 2 heterozygous trisomic genotypes. We developed a method for assigning heterozygous trisomic genotypes that uses the ratio of the height of the 2 allele peaks obtained by mass spectrometry after a single-base extension assay. Eighteen COL6A2 (collagen, type VI, alpha 2) SNPs were analyzed in euploid and trisomic individuals by means of a multiplexed single-base extension assay that generated allele-specific oligonucleotides of differing M(r) values for detection by MALDI-TOF mass spectrometry. Reference data (mean and SD) for the allele peak height ratios were determined from heterozygous euploid samples. The heterozygous trisomic genotypes were assigned by calculating the z score for each trisomic allele peak height ratio and by considering the sign (+/-) of the z score. Heterozygous trisomic genotypes were assigned in 96.1% (range, 89.9%-100%) of the samples for each SNP analyzed. The genotypes obtained were reproduced in 95 (97.5%) of 97 loci retested in a second assay. Subsequently, the origin of nondisjunction was determined in 108 (82%) of 132 family trios with a Down syndrome child. This approach enabled reliable genotyping of heterozygous trisomic samples and the determination of the origin of nondisjunction in Down syndrome family trios.

Combined effects of single-nucleotide polymorphisms in GCK, GCKR, G6PC2 and MTNR1B on fasting plasma glucose and type 2 diabetes risk

Aims/hypothesisVariation in fasting plasma glucose (FPG) within the normal range is a known risk factor for the development of type 2 diabetes. Several reports have shown that genetic variation in the genes for glucokinase (GCK), glucokinase regulatory protein (GCKR), islet-specific glucose 6 phosphatase catalytic subunit-related protein (G6PC2) and melatonin receptor type 1B (MTNR1B) is associated with FPG. In this study we examined whether these loci also contribute to type 2 diabetes susceptibility.MethodsA random selection from the Dutch New Hoorn Study was used for replication of the association with FGP (2,361 non-diabetic participants). For the genetic association study we extended the study sample with 2,628 participants with type 2 diabetes. Risk allele counting was used to calculate a four-gene risk allele score for each individual.ResultsVariants of the GCK, G6PC2 and MTNR1B genes but not GCKR were associated with FPG (all, p ≤ 0.001; GCKR, p = 0.23). Combining these four genes in a risk allele score resulted in an increase of 0.05 mmol/l (0.04–0.07) per additional risk allele (p = 2 × 10−13). Furthermore, participants with less than three or more than five risk alleles showed significantly different type 2 diabetes susceptibility compared with the most common group with four risk alleles (OR 0.77 [0.65–0.93], p = 0.005 and OR 2.05 [1.50–2.80], p = 4 × 10−6 respectively). The age at diagnosis was also significantly associated with the number of risk alleles (p = 0.009).ConclusionsA combined risk allele score for single-nucleotide polymorphisms in four known FPG loci is significantly associated with FPG and HbA1c in a Dutch population-based sample of non-diabetic participants. Carriers of low or high numbers of risk alleles show significantly different risks for type 2 diabetes compared with the reference group.Electronic supplementary materialThe online version of this article (doi:10.1007/s00125-009-1413-9) contains supplementary material, which is available to authorised users.

The Common Polymorphisms (Single Nucleotide Polymorphism [SNP] +45 and SNP +276) of the Adiponectin Gene Predict the Conversion From Impaired Glucose Tolerance to Type 2 Diabetes

Adiponectin is an adipose tissue-specific protein with insulin-sensitizing and antiatherogenic properties. Therefore, the adiponectin gene is a promising candidate gene for type 2 diabetes. We investigated the single nucleotide polymorphisms (SNPs) +45T/G and +276G/T of the adiponectin gene as predictors for the conversion from impaired glucose tolerance to type 2 diabetes in the STOP-NIDDM trial, which aimed to investigate the effect of acarbose compared with placebo on the prevention of type 2 diabetes. Compared with the TT genotype, the G-allele of SNP +45 was associated with a 1.8-fold risk for type 2 diabetes (95% CI 1.12-3.00, P = 0.015) in the placebo group. Subjects treated with placebo and simultaneously having the G-allele of SNP +45 and the T-allele of SNP +276 (the risk genotype combination) had a 4.5-fold (1.78-11.3, P = 0.001) higher risk of developing type 2 diabetes compared with subjects carrying neither of these alleles. Women carrying the risk genotype combination had an especially high risk of conversion to diabetes (odds ratio 22.2, 95% CI 2.7-183.3, P = 0.004). In conclusion, the G-allele of SNP +45 is a predictor for the conversion to type 2 diabetes. Furthermore, the combined effect of SNP +45 and SNP +276 on the development of type 2 diabetes was stronger than that of each SNP alone.