Genome-wide association study identifies eight loci associated with blood pressure

Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5 million genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N ≤ 71,225 European ancestry, N ≤ 12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N = 29,136). We identified association between systolic or diastolic blood pressure and common variants in eight regions near the CYP17A1 (P = 7 × 10(-24)), CYP1A2 (P = 1 × 10(-23)), FGF5 (P = 1 × 10(-21)), SH2B3 (P = 3 × 10(-18)), MTHFR (P = 2 × 10(-13)), c10orf107 (P = 1 × 10(-9)), ZNF652 (P = 5 × 10(-9)) and PLCD3 (P = 1 × 10(-8)) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.

The T-381C SNP in BNP gene may be modestly associated with type 2 diabetes: an updated meta-analysis in 49 279 subjects

A recent study reported an association between the brain natriuretic peptide (BNP) promoter T-381C polymorphism (rs198389) and protection against type 2 diabetes (T2D). As replication in several studies is mandatory to confirm genetic results, we analyzed the T-381C polymorphism in seven independent case-control cohorts and in 291 T2D-enriched pedigrees totalling 39 557 subjects of European origin. A meta-analysis of the seven case-control studies (n = 39 040) showed a nominal protective effect [odds ratio (OR) = 0.86 (0.79-0.94), P = 0.0006] of the CC genotype on T2D risk, consistent with the previous study. By combining all available data (n = 49 279), we further confirmed a modest contribution of the BNP T-381C polymorphism for protection against T2D [OR = 0.86 (0.80-0.92), P = 1.4 x 10(-5)]. Potential confounders such as gender, age, obesity status or family history were tested in 4335 T2D and 4179 normoglycemic subjects and they had no influence on T2D risk. This study provides further evidence of a modest contribution of the BNP T-381C polymorphism in protection against T2D and illustrates the difficulty of unambiguously proving modest-sized associations even with large sample sizes.

Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants

We conducted a genome-wide association study testing single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) for association with early-onset myocardial infarction in 2,967 cases and 3,075 controls. We carried out replication in an independent sample with an effective sample size of up to 19,492. SNPs at nine loci reached genome-wide significance: three are newly identified (21q22 near MRPS6-SLC5A3-KCNE2, 6p24 in PHACTR1 and 2q33 in WDR12) and six replicated prior observations (9p21, 1p13 near CELSR2-PSRC1-SORT1, 10q11 near CXCL12, 1q41 in MIA3, 19p13 near LDLR and 1p32 near PCSK9). We tested 554 common copy number polymorphisms (>1% allele frequency) and none met the pre-specified threshold for replication (P < 10(-3)). We identified 8,065 rare CNVs but did not detect a greater CNV burden in cases compared to controls, in genes compared to the genome as a whole, or at any individual locus. SNPs at nine loci were reproducibly associated with myocardial infarction, but tests of common and rare CNVs failed to identify additional associations with myocardial infarction risk.

New susceptibility locus for coronary artery disease on chromosome 3q22.3

We present a three-stage analysis of genome-wide SNP data in 1,222 German individuals with myocardial infarction and 1,298 controls, in silico replication in three additional genome-wide datasets of coronary artery disease (CAD) and subsequent replication in approximately 25,000 subjects. We identified one new CAD risk locus on 3q22.3 in MRAS (P = 7.44 x 10(-13); OR = 1.15, 95% CI = 1.11-1.19), and suggestive association with a locus on 12q24.31 near HNF1A-C12orf43 (P = 4.81 x 10(-7); OR = 1.08, 95% CI = 1.05-1.11).

Common variants at 30 loci contribute to polygenic dyslipidemia

Blood low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglyceride levels are risk factors for cardiovascular disease. To dissect the polygenic basis of these traits, we conducted genome-wide association screens in 19,840 individuals and replication in up to 20,623 individuals. We identified 30 distinct loci associated with lipoprotein concentrations (each with P < 5 x 10(-8)), including 11 loci that reached genome-wide significance for the first time. The 11 newly defined loci include common variants associated with LDL cholesterol near ABCG8, MAFB, HNF1A and TIMD4; with HDL cholesterol near ANGPTL4, FADS1-FADS2-FADS3, HNF4A, LCAT, PLTP and TTC39B; and with triglycerides near AMAC1L2, FADS1-FADS2-FADS3 and PLTP. The proportion of individuals exceeding clinical cut points for high LDL cholesterol, low HDL cholesterol and high triglycerides varied according to an allelic dosage score (P < 10(-15) for each trend). These results suggest that the cumulative effect of multiple common variants contributes to polygenic dyslipidemia.

Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion

Genome-wide association studies have shown that variation in MTNR1B (melatonin receptor 1B) is associated with insulin and glucose concentrations. Here we show that the risk genotype of this SNP predicts future type 2 diabetes (T2D) in two large prospective studies. Specifically, the risk genotype was associated with impairment of early insulin response to both oral and intravenous glucose and with faster deterioration of insulin secretion over time. We also show that the MTNR1B mRNA is expressed in human islets, and immunocytochemistry confirms that it is primarily localized in beta cells in islets. Nondiabetic individuals carrying the risk allele and individuals with T2D showed increased expression of the receptor in islets. Insulin release from clonal beta cells in response to glucose was inhibited in the presence of melatonin. These data suggest that the circulating hormone melatonin, which is predominantly released from the pineal gland in the brain, is involved in the pathogenesis of T2D. Given the increased expression of MTNR1B in individuals at risk of T2D, the pathogenic effects are likely exerted via a direct inhibitory effect on beta cells. In view of these results, blocking the melatonin ligand-receptor system could be a therapeutic avenue in T2D.

Variants in MTNR1B influence fasting glucose levels

To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 x 10(-50)) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 x 10(-15)). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 x 10(-7)) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 x 10(-57)) and GCK (rs4607517, P = 1.0 x 10(-25)) loci.

Genetic analysis of human traits in vitro: drug response and gene expression in lymphoblastoid cell lines

Lymphoblastoid cell lines (LCLs), originally collected as renewable sources of DNA, are now being used as a model system to study genotype–phenotype relationships in human cells, including searches for QTLs influencing levels of individual mRNAs and responses to drugs and radiation. In the course of attempting to map genes for drug response using 269 LCLs from the International HapMap Project, we evaluated the extent to which biological noise and non-genetic confounders contribute to trait variability in LCLs. While drug responses could be technically well measured on a given day, we observed significant day-to-day variability and substantial correlation to non-genetic confounders, such as baseline growth rates and metabolic state in culture. After correcting for these confounders, we were unable to detect any QTLs with genome-wide significance for drug response. A much higher proportion of variance in mRNA levels may be attributed to non-genetic factors (intra-individual variance—i.e., biological noise, levels of the EBV virus used to transform the cells, ATP levels) than to detectable eQTLs. Finally, in an attempt to improve power, we focused analysis on those genes that had both detectable eQTLs and correlation to drug response; we were unable to detect evidence that eQTL SNPs are convincingly associated with drug response in the model. While LCLs are a promising model for pharmacogenetic experiments, biological noise and in vitro artifacts may reduce power and have the potential to create spurious association due to confounding.

The use of lymphoblastoid cell lines (LCLs) has evolved from a renewable source of DNA to an in vitro model system to study the genetics of gene expression, drug response, and other traits in a controlled laboratory setting. While convincing relationships between SNPs and mRNA levels (eQTLs) have been described, the degree to which non-genetic variables also influence phenotypes in LCLs is less well characterized. In the course of attempting to map genes for drug responses in vitro, we evaluated the reproducibility of in vitro traits across replicates, the impact of the EBV virus used to transform B cells into cell lines, and the effect of in vitro culture conditions. We found that responses to at least some drugs and levels of many mRNAs can be technically well measured, but vary both across experiments and with non-genetic confounders such as growth rates, EBV levels, and ATP levels. The influence of such non-genetic factors can both decrease power to detect true relationships between DNA variation and traits and create the potential for non-genetic confounding and spurious associations between DNA variants and traits.

Clinical risk factors, DNA variants, and the development of type 2 diabetes

BACKGROUND

Type 2 diabetes mellitus is thought to develop from an interaction between environmental and genetic factors. We examined whether clinical or genetic factors or both could predict progression to diabetes in two prospective cohorts.

METHODS

We genotyped 16 single-nucleotide polymorphisms (SNPs) and examined clinical factors in 16,061 Swedish and 2770 Finnish subjects. Type 2 diabetes developed in 2201 (11.7%) of these subjects during a median follow-up period of 23.5 years. We also studied the effect of genetic variants on changes in insulin secretion and action over time.

RESULTS

Strong predictors of diabetes were a family history of the disease, an increased body-mass index, elevated liver-enzyme levels, current smoking status, and reduced measures of insulin secretion and action. Variants in 11 genes (TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX) were significantly associated with the risk of type 2 diabetes independently of clinical risk factors; variants in 8 of these genes were associated with impaired beta-cell function. The addition of specific genetic information to clinical factors slightly improved the prediction of future diabetes, with a slight increase in the area under the receiver-operating-characteristic curve from 0.74 to 0.75; however, the magnitude of the increase was significant (P=1.0x10(-4)). The discriminative power of genetic risk factors improved with an increasing duration of follow-up, whereas that of clinical risk factors decreased.

CONCLUSIONS

As compared with clinical risk factors alone, common genetic variants associated with the risk of diabetes had a small effect on the ability to predict the future development of type 2 diabetes. The value of genetic factors increased with an increasing duration of follow-up.

Genetic mapping in human disease

Genetic mapping provides a powerful approach to identify genes and biological processes underlying any trait influenced by inheritance, including human diseases. We discuss the intellectual foundations of genetic mapping of Mendelian and complex traits in humans, examine lessons emerging from linkage analysis of Mendelian diseases and genome-wide association studies of common diseases, and discuss questions and challenges that lie ahead.

Common missense variant in the glucokinase regulatory protein gene is associated with increased plasma triglyceride and C-reactive protein but lower fasting glucose concentrations

OBJECTIVE

Using the genome-wide association approach, we recently identified the glucokinase regulatory protein gene (GCKR, rs780094) region as a novel quantitative trait locus for plasma triglyceride concentration in Europeans. Here, we sought to study the association of GCKR variants with metabolic phenotypes, including measures of glucose homeostasis, to evaluate the GCKR locus in samples of non-European ancestry and to fine- map across the associated genomic interval.

RESEARCH DESIGN AND METHODS

We performed association studies in 12 independent cohorts comprising >45,000 individuals representing several ancestral groups (whites from Northern and Southern Europe, whites from the U.S., African Americans from the U.S., Hispanics of Caribbean origin, and Chinese, Malays, and Asian Indians from Singapore). We conducted genetic fine-mapping across the approximately 417-kb region of linkage disequilibrium spanning GCKR and 16 other genes on chromosome 2p23 by imputing untyped HapMap single nucleotide polymorphisms (SNPs) and genotyping 104 SNPs across the associated genomic interval.

RESULTS

We provide comprehensive evidence that GCKR rs780094 is associated with opposite effects on fasting plasma triglyceride (P(meta) = 3 x 10(-56)) and glucose (P(meta) = 1 x 10(-13)) concentrations. In addition, we confirmed recent reports that the same SNP is associated with C-reactive protein (CRP) level (P = 5 x 10(-5)). Both fine-mapping approaches revealed a common missense GCKR variant (rs1260326, Pro446Leu, 34% frequency, r(2) = 0.93 with rs780094) as the strongest association signal in the region.

CONCLUSIONS

These findings point to a molecular mechanism in humans by which higher triglycerides and CRP can be coupled with lower plasma glucose concentrations and position GCKR in central pathways regulating both hepatic triglyceride and glucose metabolism.

Whole population, genome-wide mapping of hidden relatedness

We present GERMLINE, a robust algorithm for identifying segmental sharing indicative of recent common ancestry between pairs of individuals. Unlike methods with comparable objectives, GERMLINE scales linearly with the number of samples, enabling analysis of whole-genome data in large cohorts. Our approach is based on a dictionary of haplotypes that is used to efficiently discover short exact matches between individuals. We then expand these matches using dynamic programming to identify long, nearly identical segmental sharing that is indicative of relatedness. We use GERMLINE to comprehensively survey hidden relatedness both in the HapMap as well as in a densely typed island population of 3000 individuals. We verify that GERMLINE is in concordance with other methods when they can process the data, and also facilitates analysis of larger scale studies. We bolster these results by demonstrating novel applications of precise analysis of hidden relatedness for (1) identification and resolution of phasing errors and (2) exposing polymorphic deletions that are otherwise challenging to detect. This finding is supported by concordance of detected deletions with other evidence from independent databases and statistical analyses of fluorescence intensity not used by GERMLINE.

Variations in the G6PC2/ABCB11 genomic region are associated with fasting glucose levels

Identifying the genetic variants that regulate fasting glucose concentrations may further our understanding of the pathogenesis of diabetes. We therefore investigated the association of fasting glucose levels with SNPs in 2 genome-wide scans including a total of 5,088 nondiabetic individuals from Finland and Sardinia. We found a significant association between the SNP rs563694 and fasting glucose concentrations (P = 3.5 x 10(-7)). This association was further investigated in an additional 18,436 nondiabetic individuals of mixed European descent from 7 different studies. The combined P value for association in these follow-up samples was 6.9 x 10(-26), and combining results from all studies resulted in an overall P value for association of 6.4 x 10(-33). Across these studies, fasting glucose concentrations increased 0.01-0.16 mM with each copy of the major allele, accounting for approximately 1% of the total variation in fasting glucose. The rs563694 SNP is located between the genes glucose-6-phosphatase catalytic subunit 2 (G6PC2) and ATP-binding cassette, subfamily B (MDR/TAP), member 11 (ABCB11). Our results in combination with data reported in the literature suggest that G6PC2, a glucose-6-phosphatase almost exclusively expressed in pancreatic islet cells, may underlie variation in fasting glucose, though it is possible that ABCB11, which is expressed primarily in liver, may also contribute to such variation.

Common SNPs in HMGCR in micronesians and whites associated with LDL-cholesterol levels affect alternative splicing of exon13

Background- Variation in LDL-cholesterol (LDL-C) among individuals is a complex genetic trait involving multiple genes and gene-environment interactions.

METHODS AND RESULTS

In a genome-wide association study (GWAS) to identify genetic variants influencing LDL-C in an isolated population from Kosrae, we observed associations for SNPs in the gene encoding 3hydroxy-3-methylglutaryl (HMG)-coenzyme A (CoA) reductase (HMGCR). Three of these SNPs (rs7703051, rs12654264, and rs3846663) met the statistical threshold of genome-wide significance when combined with data from the Diabetes Genetics Initiative GWAS. We followed up the association results and identified a functional SNP in intron13 (rs3846662), which was in linkage disequilibrium with the SNPs of genome-wide significance and affected alternative splicing of HMGCR mRNA. In vitro studies in human lymphoblastoid cells demonstrated that homozygosity for the rs3846662 minor allele was associated with up to 2.2-fold lower expression of alternatively spliced HMGCR mRNA lacking exon13, and minigene transfection assays confirmed that allele status at rs3846662 directly modulated alternative splicing of HMGCR exon13 (42.9+/-3.9 versus 63.7+/-1.0%Deltaexon13/total HMGCR mRNA, P=0.02). Further, the alternative splice variant could not restore HMGCR activity when expressed in HMGCR deficient UT-2 cells.

CONCLUSIONS

We identified variants in HMGCR that are associated with LDL-C across populations and affect alternative splicing of HMGCR exon13.

Common variants at CD40 and other loci confer risk of rheumatoid arthritis

To identify rheumatoid arthritis risk loci in European populations, we conducted a meta-analysis of two published genome-wide association (GWA) studies totaling 3,393 cases and 12,462 controls. We genotyped 31 top-ranked SNPs not previously associated with rheumatoid arthritis in an independent replication of 3,929 autoantibody-positive rheumatoid arthritis cases and 5,807 matched controls from eight separate collections. We identified a common variant at the CD40 gene locus (rs4810485, P = 0.0032 replication, P = 8.2 x 10(-9) overall, OR = 0.87). Along with other associations near TRAF1 (refs. 2,3) and TNFAIP3 (refs. 4,5), this implies a central role for the CD40 signaling pathway in rheumatoid arthritis pathogenesis. We also identified association at the CCL21 gene locus (rs2812378, P = 0.00097 replication, P = 2.8 x 10(-7) overall), a gene involved in lymphocyte trafficking. Finally, we identified evidence of association at four additional gene loci: MMEL1-TNFRSF14 (rs3890745, P = 0.0035 replication, P = 1.1 x 10(-7) overall), CDK6 (rs42041, P = 0.010 replication, P = 4.0 x 10(-6) overall), PRKCQ (rs4750316, P = 0.0078 replication, P = 4.4 x 10(-6) overall), and KIF5A-PIP4K2C (rs1678542, P = 0.0026 replication, P = 8.8 x 10(-8) overall).

Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs

Accurate and complete measurement of single nucleotide (SNP) and copy number (CNV) variants, both common and rare, will be required to understand the role of genetic variation in disease. We present Birdsuite, a four-stage analytical framework instantiated in software for deriving integrated and mutually consistent copy number and SNP genotypes. The method sequentially assigns copy number across regions of common copy number polymorphisms (CNPs), calls genotypes of SNPs, identifies rare CNVs via a hidden Markov model (HMM), and generates an integrated sequence and copy number genotype at every locus (for example, including genotypes such as A-null, AAB and BBB in addition to AA, AB and BB calls). Such genotypes more accurately depict the underlying sequence of each individual, reducing the rate of apparent mendelian inconsistencies. The Birdsuite software is applied here to data from the Affymetrix SNP 6.0 array. Additionally, we describe a method, implemented in PLINK, to utilize these combined SNP and CNV genotypes for association testing with a phenotype.

Integrated detection and population-genetic analysis of SNPs and copy number variation

Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.

Extension of type 2 diabetes genome-wide association scan results in the diabetes prevention program

OBJECTIVE

Genome-wide association scans (GWASs) have identified novel diabetes-associated genes. We evaluated how these variants impact diabetes incidence, quantitative glycemic traits, and response to preventive interventions in 3,548 subjects at high risk of type 2 diabetes enrolled in the Diabetes Prevention Program (DPP), which examined the effects of lifestyle intervention, metformin, and troglitazone versus placebo.

RESEARCH DESIGN AND METHODS

We genotyped selected single nucleotide polymorphisms (SNPs) in or near diabetes-associated loci, including EXT2, CDKAL1, CDKN2A/B, IGF2BP2, HHEX, LOC387761, and SLC30A8 in DPP participants and performed Cox regression analyses using genotype, intervention, and their interactions as predictors of diabetes incidence. We evaluated their effect on insulin resistance and secretion at 1 year.

RESULTS

None of the selected SNPs were associated with increased diabetes incidence in this population. After adjustments for ethnicity, baseline insulin secretion was lower in subjects with the risk genotype at HHEX rs1111875 (P = 0.01); there were no significant differences in baseline insulin sensitivity. Both at baseline and at 1 year, subjects with the risk genotype at LOC387761 had paradoxically increased insulin secretion; adjustment for self-reported ethnicity abolished these differences. In ethnicity-adjusted analyses, we noted a nominal differential improvement in beta-cell function for carriers of the protective genotype at CDKN2A/B after 1 year of troglitazone treatment (P = 0.01) and possibly lifestyle modification (P = 0.05).

CONCLUSIONS

We were unable to replicate the GWAS findings regarding diabetes risk in the DPP. We did observe genotype associations with differences in baseline insulin secretion at the HHEX locus and a possible pharmacogenetic interaction at CDKNA2/B.

Deletion polymorphism upstream of IRGM associated with altered IRGM expression and Crohn's disease

Following recent success in genome-wide association studies, a critical focus of human genetics is to understand how genetic variation at implicated loci influences cellular and disease processes. Crohn's disease (CD) is associated with SNPs around IRGM, but coding-sequence variation has been excluded as a source of this association. We identified a common, 20-kb deletion polymorphism, immediately upstream of IRGM and in perfect linkage disequilibrium (r2 = 1.0) with the most strongly CD-associated SNP, that causes IRGM to segregate in the population with two distinct upstream sequences. The deletion (CD risk) and reference (CD protective) haplotypes of IRGM showed distinct expression patterns. Manipulation of IRGM expression levels modulated cellular autophagy of internalized bacteria, a process implicated in CD. These results suggest that the CD association at IRGM arises from an alteration in IRGM regulation that affects the efficacy of autophagy and identify a common deletion polymorphism as a likely causal variant.

Genetic variants near TNFAIP3 on 6q23 are associated with systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease influenced by genetic and environmental factors. We carried out a genome-wide association scan and replication study and found an association between SLE and a variant in TNFAIP3 (rs5029939, meta-analysis P = 2.89 x 10(-12), OR = 2.29). We also found evidence of two independent signals near TNFAIP3 associated with SLE, including one previously associated with rheumatoid arthritis (RA). These results establish that variants near TNFAIP3 contribute to differential risk of SLE and RA.

Estimation of the multiple testing burden for genomewide association studies of nearly all common variants

Genomewide association studies are an exciting strategy in genetics, recently becoming feasible and harvesting many novel genes linked to multiple phenotypes. Determining the significance of results in the face of testing a genomewide set of multiple hypotheses, most of which are producing noisy, null-distributed association signals, presents a challenge to the wide community of association researchers. Rather than each study engaging in independent evaluation of significance standards, we have undertaken the task of developing such standards for genomewide significance, based on data collected by the International Haplotype Map Consortium. We report an estimated testing burden of a million independent tests genomewide in Europeans, and twice that number in Africans. We further identify the sensitivity of the testing burden to the required significance level, with implications to staged design of association studies.

Testing of diabetes-associated WFS1 polymorphisms in the Diabetes Prevention Program

AIMS/HYPOTHESIS

Wolfram syndrome (diabetes insipidus, diabetes mellitus, optic atrophy and deafness) is caused by mutations in the WFS1 gene. Recently, single nucleotide polymorphisms (SNPs) in WFS1 have been reproducibly associated with type 2 diabetes. We therefore examined the effects of these variants on diabetes incidence and response to interventions in the Diabetes Prevention Program (DPP), in which a lifestyle intervention or metformin treatment was compared with placebo.

METHODS

We genotyped the WFS1 SNPs rs10010131, rs752854 and rs734312 (H611R) in 3,548 DPP participants and performed Cox regression analysis using genotype, intervention and their interactions as predictors of diabetes incidence. We also evaluated the effect of these SNPs on insulin resistance and beta cell function at 1 year.

RESULTS

Although none of the three SNPs was associated with diabetes incidence in the overall cohort, white homozygotes for the previously reported protective alleles appeared less likely to develop diabetes in the lifestyle arm. Examination of the publicly available Diabetes Genetics Initiative genome-wide association dataset revealed that rs10012946, which is in strong linkage disequilibrium with the three WFS1 SNPs (r(2)=0.88-1.0), was associated with type 2 diabetes (allelic odds ratio 0.85, 95% CI 0.75-0.97, p=0.026). In the DPP, we noted a trend towards increased insulin secretion in carriers of the protective variants, although for most SNPs this was seen as compensatory for the diminished insulin sensitivity.

CONCLUSIONS/INTERPRETATION

The previously reported protective effect of select WFS1 alleles may be magnified by a lifestyle intervention. These variants appear to confer an improvement in beta cell function.