OBJECTIVE

Wolfram syndrome 1 (WFS1) single nucleotide polymorphisms (SNPs) are associated with risk of type 2 diabetes. In this study we aimed to refine this association and investigate the role of low-frequency WFS1 variants in type 2 diabetes risk.

RESEARCH DESIGN AND METHODS

For fine-mapping, we sequenced WFS1 exons, splice junctions, and conserved noncoding sequences in samples from 24 type 2 diabetic case and 68 control subjects, selected tagging SNPs, and genotyped these in 959 U.K. type 2 diabetic case and 1,386 control subjects. The same genomic regions were sequenced in samples from 1,235 type 2 diabetic case and 1,668 control subjects to compare the frequency of rarer variants between case and control subjects.

RESULTS

Of 31 tagging SNPs, the strongest associated was the previously untested 3′ untranslated region rs1046320 (P = 0.008); odds ratio 0.84 and P = 6.59 × 10−7 on further replication in 3,753 case and 4,198 control subjects. High correlation between rs1046320 and the original strongest SNP (rs10010131) (r2 = 0.92) meant that we could not differentiate between their effects in our samples. There was no difference in the cumulative frequency of 82 rare (minor allele frequency [MAF] <0.01) nonsynonymous variants between type 2 diabetic case and control subjects (P = 0.79). Two intermediate frequency (MAF 0.01–0.05) nonsynonymous changes also showed no statistical association with type 2 diabetes.

CONCLUSIONS

We identified six highly correlated SNPs that show strong and comparable associations with risk of type 2 diabetes, but further refinement of these associations will require large sample sizes (>100,000) or studies in ethnically diverse populations. Low frequency variants in WFS1 are unlikely to have a large impact on type 2 diabetes risk in white U.K. populations, highlighting the complexities of undertaking association studies with low-frequency variants identified by resequencing.

OBJECTIVE

WFS1 (Wolfram Syndrome 1) SNPs are associated with risk of type 2 diabetes (T2D). Here, we aimed to refine this association and investigate the role of low frequency WFS1 variants in T2D risk.

RESEARCH DESIGN AND METHODS

For fine-mapping, we sequenced WFS1 exons, splice junctions and conserved non-coding sequences in 24 T2D cases and 68 controls, selected tagging SNPs, and genotyped these in 959 UK T2D cases and 1386 controls. The same genomic regions were sequenced in 1235 T2D cases and 1668 controls to compare the frequency of rarer variants between cases and controls.

RESULTS

Of 31 tagging SNPs, the strongest associated was the previously untested 3′ UTR rs1046320 (P=0.008); OR=0.84, P=6.59 × 10−7 on further replication in 3753 cases and 4198 controls. High correlation between rs1046320 and the original strongest SNP (rs10010131) (r2=0.92) meant that we could not differentiate between their effects in our samples. There was no difference in the cumulative frequency of 82 rare (MAF<0.01) non-synonymous variants between T2D cases and controls (P=0.79). Two intermediate frequency (MAF 0.01-0.05) non-synonymous changes also showed no statistical association with T2D.

CONCLUSION

We identified six highly correlated SNPs that show strong and comparable associations with risk of T2D association but further refinement of these associations will require large sample sizes (>100,000), or studies in ethnically diverse populations. Low frequency variants in WFS1 are unlikely to have a large impact on T2D risk in white UK populations, highlighting the complexities of undertaking association studies with low frequency variants identified by re-sequencing.

For most associations of common single nucleotide polymorphisms (SNPs) with common diseases, the genetic model of inheritance is unknown. The authors extended and applied a Bayesian meta-analysis approach to data from 19 studies on 17 replicated associations with type 2 diabetes. For 13 SNPs, the data fitted very well to an additive model of inheritance for the diabetes risk allele; for 4 SNPs, the data were consistent with either an additive model or a dominant model; and for 2 SNPs, the data were consistent with an additive or recessive model. Results were robust to the use of different priors and after exclusion of data for which index SNPs had been examined indirectly through proxy markers. The Bayesian meta-analysis model yielded point estimates for the genetic effects that were very similar to those previously reported based on fixed- or random-effects models, but uncertainty about several of the effects was substantially larger. The authors also examined the extent of between-study heterogeneity in the genetic model and found generally small between-study deviation values for the genetic model parameter. Heterosis could not be excluded for 4 SNPs. Information on the genetic model of robustly replicated association signals derived from genome-wide association studies may be useful for predictive modeling and for designing biologic and functional experiments.

A mendelian randomization study based on data from multiple cohorts conducted by Karani Santhanakrishnan Vimaleswaran and colleagues re-examines the causal nature of the relationship between vitamin D levels and obesity.

Background

Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis.

Methods and Findings

We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects.

Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) and 25(OH)D (−0.06% [95% CI −0.10 to −0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10−57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: −4.2 [95% CI −7.1 to −1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores).

Conclusions

On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.

Please see later in the article for the Editors' Summary

Editors' Summary

Background

Obesity—having an unhealthy amount of body fat—is increasing worldwide. In the US, for example, a third of the adult population is now obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Although there is a genetic contribution to obesity, people generally become obese by consuming food and drink that contains more energy than they need for their daily activities. Thus, obesity can be prevented by having a healthy diet and exercising regularly. Compared to people with a healthy weight, obese individuals have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. They also have a higher risk of vitamin D deficiency, another increasingly common public health concern. Vitamin D, which is essential for healthy bones as well as other functions, is made in the skin after exposure to sunlight but can also be obtained through the diet and through supplements.

Why Was This Study Done?

Observational studies cannot prove that obesity causes vitamin D deficiency because obese individuals may share other characteristics that reduce their circulating 25-hydroxy vitamin D [25(OH)D] levels (referred to as confounding). Moreover, observational studies cannot indicate whether the larger vitamin D storage capacity of obese individuals (vitamin D is stored in fatty tissues) lowers their 25(OH)D levels or whether 25(OH)D levels influence fat accumulation (reverse causation). If obesity causes vitamin D deficiency, monitoring and treating vitamin D deficiency might alleviate some of the adverse health effects of obesity. Conversely, if low vitamin D levels cause obesity, encouraging people to take vitamin D supplements might help to control the obesity epidemic. Here, the researchers use bi-directional “Mendelian randomization” to examine the direction and causality of the relationship between BMI and 25(OH)D. In Mendelian randomization, causality is inferred from associations between genetic variants that mimic the influence of a modifiable environmental exposure and the outcome of interest. Because gene variants do not change over time and are inherited randomly, they are not prone to confounding and are free from reverse causation. Thus, if a lower vitamin D status leads to obesity, genetic variants associated with lower 25(OH)D concentrations should be associated with higher BMI, and if obesity leads to a lower vitamin D status, then genetic variants associated with higher BMI should be associated with lower 25(OH)D concentrations.

What Did the Researchers Do and Find?

The researchers created a “BMI allele score” based on 12 BMI-related gene variants and two “25(OH)D allele scores,” which are based on gene variants that affect either 25(OH)D synthesis or breakdown. Using information on up to 42,024 participants from 21 studies, the researchers showed that the BMI allele score was associated with both BMI and with 25(OH)D levels among the study participants. Based on this information, they calculated that each 10% increase in BMI will lead to a 4.2% decrease in 25(OH)D concentrations. By contrast, although both 25(OH)D allele scores were strongly associated with 25(OH)D levels, neither score was associated with BMI. This lack of an association between 25(OH)D allele scores and obesity was confirmed using data from more than 100,000 individuals involved in 46 studies that has been collected by the GIANT (Genetic Investigation of Anthropometric Traits) consortium.

What Do These Findings Mean?

These findings suggest that a higher BMI leads to a lower vitamin D status whereas any effects of low vitamin D status on BMI are likely to be small. That is, these findings provide evidence for obesity as a causal factor in the development of vitamin D deficiency but not for vitamin D deficiency as a causal factor in the development of obesity. These findings suggest that population-level interventions to reduce obesity should lead to a reduction in the prevalence of vitamin D deficiency and highlight the importance of monitoring and treating vitamin D deficiency as a means of alleviating the adverse influences of obesity on health.

Additional Information

Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001383.

The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish); a data brief provides information about the vitamin D status of the US population

The World Health Organization provides information on obesity (in several languages)

The UK National Health Service Choices website provides detailed information about obesity and a link to a personal story about losing weight; it also provides information about vitamin D

The International Obesity Taskforce provides information about the global obesity epidemic

The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)

The US Office of Dietary Supplements provides information about vitamin D (in English and Spanish)

MedlinePlus has links to further information about obesity and about vitamin D (in English and Spanish)

Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)

Overview and details of the collaborative large-scale genetic association study (D-CarDia) provide information about vitamin D and the risk of cardiovascular disease, diabetes and related traits

OBJECTIVE

To investigate whether associations of common genetic variants recently identified for fasting glucose or insulin levels in nondiabetic adults are detectable in healthy children and adolescents.

RESEARCH DESIGN AND METHODS

A total of 16 single nucleotide polymorphisms (SNPs) associated with fasting glucose were genotyped in six studies of children and adolescents of European origin, including over 6,000 boys and girls aged 9–16 years. We performed meta-analyses to test associations of individual SNPs and a weighted risk score of the 16 loci with fasting glucose.

RESULTS

Nine loci were associated with glucose levels in healthy children and adolescents, with four of these associations reported in previous studies and five reported here for the first time (GLIS3, PROX1, SLC2A2, ADCY5, and CRY2). Effect sizes were similar to those in adults, suggesting age-independent effects of these fasting glucose loci. Children and adolescents carrying glucose-raising alleles of G6PC2, MTNR1B, GCK, and GLIS3 also showed reduced β-cell function, as indicated by homeostasis model assessment of β-cell function. Analysis using a weighted risk score showed an increase [β (95% CI)] in fasting glucose level of 0.026 mmol/L (0.021–0.031) for each unit increase in the score.

CONCLUSIONS

Novel fasting glucose loci identified in genome-wide association studies of adults are associated with altered fasting glucose levels in healthy children and adolescents with effect sizes comparable to adults. In nondiabetic adults, fasting glucose changes little over time, and our results suggest that age-independent effects of fasting glucose loci contribute to long-term interindividual differences in glucose levels from childhood onwards.

Background

Vitamin D is crucial for maintaining musculoskeletal health. Recently, vitamin D insufficiency has been linked to a number of extraskeletal disorders, including diabetes, cancer, and cardiovascular disease. Determinants of circulating 25-hydroxyvitamin D (25-OH D) include sun exposure and dietary intake, but its high heritability suggests that genetic determinants may also play a role.

Methods

We performed a genome-wide association study of 25-OH D among ∼30,000 individuals of European descent from 15 cohorts. Five cohorts were designated as discovery cohorts (n=16,125), five as in silico replication cohorts (n=9,366), and five as de novo replication cohorts (n=8,378). Association results were combined using z-score-weighted meta-analysis. Vitamin D insufficiency was defined as 25-OH D <75 nmol/L or <50 nmol/L.

Findings

Variants at three loci reached genome-wide significance in the discovery cohorts, and were confirmed in the replication cohorts: 4p12 (overall P=1.9 × 10-109 for rs2282679, in GC); 11q12 (P=2.1 × 10-27 for rs12785878, near DHCR7); 11p15 (P=3.3 × 10-20 for rs10741657, near CYP2R1). Variants at an additional locus (20q13, CYP24A1) were genome-wide significant in the pooled sample (P=6.0 × 10-10 for rs6013897). A genotype score was constructed using the three confirmed variants. Those in the top quartile of genotype scores had 2- to 2.5-fold elevated odds of vitamin D insufficiency (P≤1 × 10-26).

Interpretation

Variants near genes involved in cholesterol synthesis (DHCR7), hydroxylation (CYP2R1, CYP24A1), and vitamin D transport (GC) influence vitamin D status. Genetic variation at these loci identifies individuals of European descent who have substantially elevated risk of vitamin D insufficiency.

For most associations of common polymorphisms with common diseases, the genetic model of inheritance is unknown. We extended and applied a Bayesian meta-analysis approach to data from 19 studies on 17 replicated associations for type 2 diabetes. For 13 polymorphisms, the data fit very well to an additive model, for 4 polymorphisms the data were consistent with either an additive or dominant model, and for 2 polymorphisms with an additive or recessive model of inheritance for the diabetes risk allele. Results were robust to using different priors and after excluding data where index polymorphisms had been examined indirectly through proxy markers. The Bayesian meta-analysis model yielded point estimates for the genetic effects that are very similar to those previously reported based on fixed or random effects models, but uncertainty about several of the effects was substantially larger. We also examined the extent of between-study heterogeneity in the genetic model and found generally small values of the between-study deviation for the genetic model parameter. Heterosis could not be excluded in 4 SNPs. Information on the genetic model of robustly replicated GWA-derived association signals may be useful for predictive modeling, and for designing biological and functional experiments.

OBJECTIVE—Single nucleotide polymorphisms (SNPs) in the P2 promoter region of HNF4A were originally shown to be associated with predisposition for type 2 diabetes in Finnish, Ashkenazi, and, more recently, Scandinavian populations, but they generated conflicting results in additional populations. We aimed to investigate whether data from a large-scale mapping approach would replicate this association in novel Ashkenazi samples and in U.K. populations and whether these data would allow us to refine the association signal.

RESEARCH DESIGN AND METHODS—Using a dense linkage disequilibrium map of 20q, we selected SNPs from a 10-Mb interval centered on HNF4A. In a staged approach, we first typed 4,608 SNPs in case-control populations from four U.K. populations and an Ashkenazi population (n = 2,516). In phase 2, a subset of 763 SNPs was genotyped in 2,513 additional samples from the same populations.

RESULTS—Combined analysis of both phases demonstrated association between HNF4A P2 SNPs (rs1884613 and rs2144908) and type 2 diabetes in the Ashkenazim (n = 991; P < 1.6 × 10−6). Importantly, these associations are significant in a subset of Ashkenazi samples (n = 531) not previously tested for association with P2 SNPs (odds ratio [OR] ∼1.7; P < 0.002), thus providing replication within the Ashkenazim. In the U.K. populations, this association was not significant (n = 4,022; P > 0.5), and the estimate for the OR was much smaller (OR 1.04; [95%CI 0.91–1.19]).

CONCLUSIONS—These data indicate that the risk conferred by HNF4A P2 is significantly different between U.K. and Ashkenazi populations (P < 0.00007), suggesting that the underlying causal variant remains unidentified. Interactions with other genetic or environmental factors may also contribute to this difference in risk between populations.

OBJECTIVE

Single nucleotide polymorphisms (SNPs) in the P2 promoter region of HNF4A were originally shown to be associated with predisposition for type 2 diabetes in Finnish, Ashkenazi, and, more recently, Scandinavian populations, but they generated conflicting results in additional populations. We aimed to investigate whether data from a large-scale mapping approach would replicate this association in novel Ashkenazi samples and in U.K. populations and whether these data would allow us to refine the association signal.

RESEARCH DESIGN AND METHODS

Using a dense linkage disequilibrium map of 20q, we selected SNPs from a 10-Mb interval centered on HNF4A. In a staged approach, we first typed 4,608 SNPs in case-control populations from four U.K. populations and an Ashkenazi population (n = 2,516). In phase 2, a subset of 763 SNPs was genotyped in 2,513 additional samples from the same populations.

RESULTS

Combined analysis of both phases demonstrated association between HNF4A P2 SNPs (rs1884613 and rs2144908) and type 2 diabetes in the Ashkenazim (n = 991; P < 1.6 × 10−6). Importantly, these associations are significant in a subset of Ashkenazi samples (n = 531) not previously tested for association with P2 SNPs (odds ratio [OR] ~1.7; P < 0.002), thus providing replication within the Ashkenazim. In the U.K. populations, this association was not significant (n = 4,022; P > 0.5), and the estimate for the OR was much smaller (OR 1.04; [95%CI 0.91-1.19]).

CONCLUSIONS

These data indicate that the risk conferred by HNF4A P2 is significantly different between U.K. and Ashkenazi populations (P < 0.00007), suggesting that the underlying causal variant remains unidentified. Interactions with other genetic or environmental factors may also contribute to this difference in risk between populations.