Estimating sleep parameters using an accelerometer without sleep diary.

Wrist worn raw-data accelerometers are used increasingly in large-scale population research. We examined whether sleep parameters can be estimated from these data in the absence of sleep diaries. Our heuristic algorithm uses the variance in estimated z-axis angle and makes basic assumptions about sleep interruptions. Detected sleep period time window (SPT-window) was compared against sleep diary in 3752 participants (range = 60-82 years) and polysomnography in sleep clinic patients (N = 28) and in healthy good sleepers (N = 22). The SPT-window derived from the algorithm was 10.9 and 2.9 minutes longer compared with sleep diary in men and women, respectively. Mean C-statistic to detect the SPT-window compared to polysomnography was 0.86 and 0.83 in clinic-based and healthy sleepers, respectively. We demonstrated the accuracy of our algorithm to detect the SPT-window. The value of this algorithm lies in studies such as UK Biobank where a sleep diary was not used.

International cancer seminars: a focus on kidney cancer.

Recent years have seen important advances in our understanding of the etiology, biology and genetics of kidney cancer. To summarize important achievements and identify prominent research questions that remain, a workshop was organized by IARC and the US NCI. A series of 'difficult questions' were formulated, which should be given future priority in the areas of population, genomic and clinical research.

Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes.

AIMS/HYPOTHESIS: Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) >1% with common metabolic phenotypes. METHODS: The study comprised three stages. We performed medium-depth (8×) whole exome sequencing in 1,000 cases with type 2 diabetes, BMI >27.5 kg/m(2) and hypertension and in 1,000 controls (stage 1). We selected 16,192 polymorphisms nominally associated (p < 0.05) with case-control status, from four selected annotation categories or from loci reported to associate with metabolic traits. These variants were genotyped in 15,989 Danes to search for association with 12 metabolic phenotypes (stage 2). In stage 3, polymorphisms showing potential associations were genotyped in a further 63,896 Europeans. RESULTS: Exome sequencing identified 70,182 polymorphisms with MAF >1%. In stage 2 we identified 51 potential associations with one or more of eight metabolic phenotypes covered by 45 unique polymorphisms. In meta-analyses of stage 2 and stage 3 results, we demonstrated robust associations for coding polymorphisms in CD300LG (fasting HDL-cholesterol: MAF 3.5%, p = 8.5 × 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 × 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 × 10(-10)). CONCLUSIONS/INTERPRETATION: We applied exome sequencing as a basis for finding genetic determinants of metabolic traits and show the existence of low-frequency and common coding polymorphisms with impact on common metabolic traits. Based on our study, coding polymorphisms with MAF above 1% do not seem to have particularly high effect sizes on the measured metabolic traits.

Multiple genetic variants explain measurable variance in type 2 diabetes-related traits in Pakistanis.

AIMS/HYPOTHESIS: Multiple genetic variants are associated with type 2 diabetes-related traits in Europeans, but their role in South Asian populations needs further study. We hypothesised that genetic variants associated with diabetes-related traits in Europeans would explain a similar proportion of phenotypic variance in a Pakistani population and could be used in Mendelian randomisation analyses. METHODS: We used data from 2,131 individuals from the Control of Blood Pressure and Risk Attenuation Trial (COBRA) in Karachi, Pakistan. Individuals were aged 40 years or older. RESULTS: Combining information from multiple genetic variants showed that fasting glucose, BMI, triacylglycerol, and systolic and diastolic blood pressure variants explained 2.9%, 0.7%, 5.5%, 1.2% and 1.8% of the variance in those traits respectively. Genetic risk scores of fasting glucose, triacylglycerol, BMI, systolic blood pressure and diastolic blood pressure variants were associated with these traits, with per allele SD effects of 0.057 (95% CI 0.041, 0.074), p=3.44 × 10(-12), 0.130 (95% CI 0.105, 0.155), p=2.9 × 10(-21), 0.04 (95% CI 0.014, 0.072), p=0.004, 0.031 (95% CI 0.016, 0.047), p=7.9 × 10(-5), 0.028 (95% CI 0.015, 0.042), p = 5.5 × 10(-5), respectively. These effects are consistent with those observed in Europeans, except that the effect of triacylglycerol variants in South Asians was slightly lower. Mendelian randomisation provided evidence that genetically influenced, raised triacylglycerol levels do not causally affect type 2 diabetes risk to the extent predicted from observational data (p=0.0003 for difference between observed and instrumental variables correlations). CONCLUSIONS/INTERPRETATION: Genetic variants identified in Europeans are associated with type 2 diabetes-related traits in Pakistanis, with comparable effect sizes. Larger studies are needed to perform adequately powered Mendelian randomisation and help dissect the relationships between type 2 diabetes-related traits in diverse South Asian subgroups.

Sequencing PDX1 (insulin promoter factor 1) in 1788 UK individuals found 5% had a low frequency coding variant, but these variants are not associated with Type 2 diabetes.

AIM: Genome-wide association studies have identified >30 common variants associated with Type 2 diabetes (>5% minor allele frequency). These variants have small effects on individual risk and do not account for a large proportion of the heritable component of the disease. Monogenic forms of diabetes are caused by mutations that occur in <1:2000 individuals and follow strict patterns of inheritance. In contrast, the role of low frequency genetic variants (minor allele frequency 0.1-5%) in Type 2 diabetes is not known. The aim of this study was to assess the role of low frequency PDX1 (also called IPF1) variants in Type 2 diabetes. METHODS: We sequenced the coding and flanking intronic regions of PDX1 in 910 patients with Type 2 diabetes and 878 control subjects. RESULTS: We identified a total of 26 variants that occurred in 5.3% of individuals, 14 of which occurred once. Only D76N occurred in >1%. We found no difference in carrier frequency between patients (5.7%) and control subjects (5.0%) (P=0.46). There were also no differences between patients and control subjects when analyses were limited to subsets of variants. The strongest subset were those variants in the DNA binding domain where all five variants identified were only found in patients (P=0.06). CONCLUSION: Approximately 5% of UK individuals carry a PDX1 variant, but there is no evidence that these variants, either individually or cumulatively, predispose to Type 2 diabetes. Further studies will need to consider strategies to assess the role of multiple variants that occur in <1 in 1000 individuals.

An FTO variant is associated with Type 2 diabetes in South Asian populations after accounting for body mass index and waist circumference.

AIMS: A common variant, rs9939609, in the FTO (fat mass and obesity) gene is associated with adiposity in Europeans, explaining its relationship with diabetes. However, data are inconsistent in South Asians. Our aim was to investigate the association of the FTO rs9939609 variant with obesity, obesity-related traits and Type 2 diabetes in South Asian individuals, and to use meta-analyses to attempt to clarify to what extent BMI influences the association of FTO variants with diabetes in South Asians. METHODS: We analysed rs9939609 in two studies of Pakistani individuals: 1666 adults aged ≥40 years from the Karachi population-based Control of Blood Pressure and Risk Attenuation (COBRA) study and 2745 individuals of Punjabi ancestry who were part of a Type 2 diabetes case-control study (UK Asian Diabetes Study/Diabetes Genetics in Pakistan; UKADS/DGP). The main outcomes were BMI, waist circumference and diabetes. Regression analyses were performed to determine associations between FTO alleles and outcomes. Summary estimates were combined in a meta-analysis of 8091 South Asian individuals (3919 patients with Type 2 diabetes and 4172 control subjects), including those from two previous studies. RESULTS: In the 4411 Pakistani individuals from this study, the age-, sex- and diabetes-adjusted association of FTO variant rs9939609 with BMI was 0.45 (95%CI 0.24-0.67) kg/m(2) per A-allele (P=3.0 × 10(-5) ) and with waist circumference was 0.88 (95% CI 0.36-1.41) cm per A-allele (P=0.001). The A-allele (30% frequency) was also significantly associated with Type 2 diabetes [per A-allele odds ratio (95%CI) 1.18 (1.07-1.30); P=0.0009]. A meta-analysis of four South Asian studies with 8091 subjects showed that the FTO A-allele predisposes to Type 2 diabetes [1.22 (95%CI 1.14-1.31); P=1.07 × 10(-8) ] even after adjusting for BMI [1.18 (95%CI 1.10-1.27); P=1.02 × 10(-5) ] or waist circumference [1.18 (95%CI 1.10-1.27); P=3.97 × 10(-5) ]. CONCLUSIONS: The strong association between FTO genotype and BMI and waist circumference in South Asians is similar to that observed in Europeans. In contrast, the strong association of FTO genotype with diabetes is only partly accounted for by BMI.

A role for coding functional variants in HNF4A in type 2 diabetes susceptibility.

AIMS/HYPOTHESIS: Rare mutations in the gene HNF4A, encoding the transcription factor hepatocyte nuclear factor 4α (HNF-4A), account for ~5% of cases of MODY and more frequent variants in this gene may be involved in multifactorial forms of diabetes. Two low-frequency, non-synonymous variants in HNF4A (V255M, minor allele frequency [MAF] ~0.1%; T130I, MAF ~3.0%)-known to influence downstream HNF-4A target gene expression-are of interest, but previous type 2 diabetes association reports were inconclusive. We aimed to evaluate the contribution of these variants to type 2 diabetes susceptibility through large-scale association analysis. METHODS: We genotyped both variants in at least 5,745 cases and 14,756 population controls from the UK and Denmark. We also undertook an expanded association analysis that included previously reported and novel genotype data obtained in Danish, Finnish, Canadian and Swedish samples. A meta-analysis incorporating all published association studies of the T130I variant was subsequently carried out in a maximum sample size of 14,279 cases and 26,835 controls. RESULTS: We found no association between V255M and type 2 diabetes in either the initial (p = 0.28) or the expanded analysis (p = 0.44). However, T130I demonstrated a modest association with type 2 diabetes in the UK and Danish samples (additive per allele OR 1.17 [95% CI 1.08-1.28]; p = 1.5 × 10⁻4), which was strengthened in the meta-analysis (OR 1.20 [95% CI 1.10-1.30]; p = 2.1 × 10⁻5). CONCLUSIONS/INTERPRETATION: Our data are consistent with T130I as a low-frequency variant influencing type 2 diabetes risk, but are not conclusive when judged against stringent standards for genome-wide significance. This study exemplifies the difficulties encountered in association testing of low-frequency variants.

C-reactive protein levels and body mass index: elucidating direction of causation through reciprocal Mendelian randomization.

CONTEXT: The assignment of direction and causality within networks of observational associations is problematic outside randomized control trials, and the presence of a causal relationship between body mass index (BMI) and C-reactive protein (CRP) is disputed. OBJECTIVE: Using reciprocal Mendelian randomization, we aim to assess the direction of causality in relationships between BMI and CRP and to demonstrate this as a promising analytical technique. PARTICIPANTS AND METHODS: The study was based on a large, cross-sectional European study from Copenhagen, Denmark. Genetic associates of BMI (FTO(rs9939609)) and circulating CRP (CRP(rs3091244)) have been used to reexamine observational associations between them. RESULTS: Observational analyses showed a strong, positive association between circulating CRP and BMI (change in BMI for a doubling in log CRP of 1.03 kg m(-2) (95% confidence interval (95% CI): 1.00, 1.07), P<0.0001). Analysis using CRP(rs3091244) to re-estimate the causal effect of circulating CRP on BMI yielded null effects (change in BMI for a doubling in log CRP of -0.24 kg m(-2) (95% CI: -0.58, 0.11), P=0.2). In contrast, analysis using FTO(rs9939609) to assess the causal effect of BMI on circulating CRP confirmed observational associations (ratio of geometric means of CRP per s.d. increase in BMI 1.41 (95% CI: 1.10, 1.80), P=0.006). CONCLUSIONS: Taken together, these data suggest that the observed association between circulating CRP and measured BMI is likely to be driven by BMI, with CRP being a marker of elevated adiposity. More generally, the method of reciprocal randomization has general applicability in determining the direction of causation within inter-correlated networks of metabolic components.

Assessing association of common variation in the C1Q gene cluster with systemic lupus erythematosus.

Recent studies have tested genetic variation at the C1QA, C1QB and C1QC (complement component 1, q subcomponent, A chain, complement component 1, q subcomponent, B chain and complement component 1, q subcomponent, c chain) loci in relation to systemic lupus erythematosus (SLE) risk. Evidence for a significant effect of C1Q locus gene polymorphisms on SLE predisposition remains unclear. We aimed to identify associations between common C1Q polymorphisms and SLE risk and serum C1q, C3 and C4 levels. We performed family-based association tests in 295 nuclear families with one affected proband. Tag-single nucleotide polymorphisms (SNPs) ranging from 35.4 kb upstream of the C1QA gene to 28 kb downstream of the C1QB gene were selected to represent the entire C1Q gene locus. We performed transmission disequilibrium tests for affectation status and continuous traits, including C1q, C3 and C4 levels using family-based association tests (FBAT). There was no evidence for a significant role of C1Q locus gene polymorphisms in SLE risk predisposition. The strongest association was observed with a variant in the 3'UTR region of the C1QB gene (rs294223, P = 0.06). We found nominally significant associations with a second variant (rs7549888) in the 3'UTR region of the C1QB gene and C1q (P = 0.01), C3 (P = 0.004) and C4 levels (P = 0.01). In a large family-based association study of C1Q gene cluster polymorphisms no evidence for a genetic role of C1Q locus SNP in SLE risk predisposition was obtained in patients of European ancestry. This is in contrast to other cohorts, in which single variants associated with C1Q, C3 and C4 levels and nephritis have been studied and shown associations.

Genetic association analysis of LARS2 with type 2 diabetes.

AIMS/HYPOTHESIS: LARS2 has been previously identified as a potential type 2 diabetes susceptibility gene through the low-frequency H324Q (rs71645922) variant (minor allele frequency [MAF] 3.0%). However, this association did not achieve genome-wide levels of significance. The aim of this study was to establish the true contribution of this variant and common variants in LARS2 (MAF > 5%) to type 2 diabetes risk. METHODS: We combined genome-wide association data (n = 10,128) from the DIAGRAM consortium with independent data derived from a tagging single nucleotide polymorphism (SNP) approach in Dutch individuals (n = 999) and took forward two SNPs of interest to replication in up to 11,163 Dutch participants (rs17637703 and rs952621). In addition, because inspection of genome-wide association study data identified a cluster of low-frequency variants with evidence of type 2 diabetes association, we attempted replication of rs9825041 (a proxy for this group) and the previously identified H324Q variant in up to 35,715 participants of European descent. RESULTS: No association between the common SNPs in LARS2 and type 2 diabetes was found. Our replication studies for the two low-frequency variants, rs9825041 and H324Q, failed to confirm an association with type 2 diabetes in Dutch, Scandinavian and UK samples (OR 1.03 [95% CI 0.95-1.12], p = 0.45, n = 31,962 and OR 0.99 [0.90-1.08], p = 0.78, n = 35,715 respectively). CONCLUSIONS/INTERPRETATION: In this study, the largest study examining the role of sequence variants in LARS2 in type 2 diabetes susceptibility, we found no evidence to support previous data indicating a role in type 2 diabetes susceptibility.

Circulating beta-carotene levels and type 2 diabetes-cause or effect?

AIMS/HYPOTHESIS: Circulating beta-carotene levels are inversely associated with risk of type 2 diabetes, but the causal direction of this association is not certain. In this study we used a Mendelian randomisation approach to provide evidence for or against the causal role of the antioxidant vitamin beta-carotene in type 2 diabetes. METHODS: We used a common polymorphism (rs6564851) near the BCMO1 gene, which is strongly associated with circulating beta-carotene levels (p = 2 x 10(-24)), with each G allele associated with a 0.27 standard deviation increase in levels. We used data from the InCHIANTI and Uppsala Longitudinal Study of Adult Men (ULSAM) studies to estimate the association between beta-carotene levels and type 2 diabetes. We next used a triangulation approach to estimate the expected effect of rs6564851 on type 2 diabetes risk and compared this with the observed effect using data from 4549 type 2 diabetes patients and 5579 controls from the Diabetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium. RESULTS: A 0.27 standard deviation increase in beta-carotene levels was associated with an OR of 0.90 (95% CI 0.86-0.95) for type 2 diabetes in the InCHIANTI study. This association was similar to that of the ULSAM study (OR 0.90 [0.84-0.97]). In contrast, there was no association between rs6564851 and type 2 diabetes (OR 0.98 [0.93-1.04], p = 0.58); this effect size was also smaller than that expected, given the known associations between rs6564851 and beta-carotene levels, and the associations between beta-carotene levels and type 2 diabetes. CONCLUSIONS/INTERPRETATION: Our findings in this Mendelian randomisation study are in keeping with randomised controlled trials suggesting that beta-carotene is not causally protective against type 2 diabetes.

Is the thrifty genotype hypothesis supported by evidence based on confirmed type 2 diabetes- and obesity-susceptibility variants?

AIMS/HYPOTHESIS: According to the thrifty genotype hypothesis, the high prevalence of type 2 diabetes and obesity is a consequence of genetic variants that have undergone positive selection during historical periods of erratic food supply. The recent expansion in the number of validated type 2 diabetes- and obesity-susceptibility loci, coupled with access to empirical data, enables us to look for evidence in support (or otherwise) of the thrifty genotype hypothesis using proven loci. METHODS: We employed a range of tests to obtain complementary views of the evidence for selection: we determined whether the risk allele at associated 'index' single-nucleotide polymorphisms is derived or ancestral, calculated the integrated haplotype score (iHS) and assessed the population differentiation statistic fixation index (F (ST)) for 17 type 2 diabetes and 13 obesity loci. RESULTS: We found no evidence for significant differences for the derived/ancestral allele test. None of the studied loci showed strong evidence for selection based on the iHS score. We find a high F (ST) for rs7901695 at TCF7L2, the largest type 2 diabetes effect size found to date. CONCLUSIONS/INTERPRETATION: Our results provide some evidence for selection at specific loci, but there are no consistent patterns of selection that provide conclusive confirmation of the thrifty genotype hypothesis. Discovery of more signals and more causal variants for type 2 diabetes and obesity is likely to allow more detailed examination of these issues.

Common genetic variation in the melatonin receptor 1B gene (MTNR1B) is associated with decreased early-phase insulin response.

AIMS/HYPOTHESIS: We investigated whether variation in MTNR1B, which was recently identified as a common genetic determinant of fasting glucose levels in healthy, diabetes-free individuals, is associated with measures of beta cell function and whole-body insulin sensitivity. METHODS: We studied 1,276 healthy individuals of European ancestry at 19 centres of the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study. Whole-body insulin sensitivity was assessed by euglycaemic-hyperinsulinaemic clamp and indices of beta cell function were derived from a 75 g oral glucose tolerance test (including 30 min insulin response and glucose sensitivity). We studied rs10830963 in MTNR1B using additive genetic models, adjusting for age, sex and recruitment centre. RESULTS: The minor (G) allele of rs10830963 in MTNR1B (frequency 0.30 in HapMap Centre d'Etude du Polymorphisme [Utah residents with northern and western European ancestry] [CEU]; 0.29 in RISC participants) was associated with higher levels of fasting plasma glucose (standardised beta [95% CI] 0.17 [0.085, 0.25] per G allele, p = 5.8 x 10(-5)), consistent with recent observations. In addition, the G-allele was significantly associated with lower early insulin response (-0.19 [-0.28, -0.10], p = 1.7 x 10(-5)), as well as with decreased beta cell glucose sensitivity (-0.11 [-0.20, -0.027], p = 0.010). No associations were observed with clamp-assessed insulin sensitivity (p = 0.15) or different measures of body size (p > 0.7 for all). CONCLUSIONS/INTERPRETATION: Genetic variation in MTNR1B is associated with defective early insulin response and decreased beta cell glucose sensitivity, which may contribute to the higher glucose levels of non-diabetic individuals carrying the minor G allele of rs10830963 in MTNR1B.

FTO gene variants are strongly associated with type 2 diabetes in South Asian Indians.

AIMS AND HYPOTHESIS: Variants of the FTO (fat mass and obesity associated) gene are associated with obesity and type 2 diabetes in white Europeans, but these associations are not consistent in Asians. A recent study in Asian Indian Sikhs showed an association with type 2 diabetes that did not seem to be mediated through BMI. We studied the association of FTO variants with type 2 diabetes and measures of obesity in South Asian Indians in Pune. METHODS: We genotyped, by sequencing, two single nucleotide polymorphisms, rs9939609 and rs7191344, in the FTO gene in 1,453 type 2 diabetes patients and 1,361 controls from Pune, Western India and a further 961 population-based individuals from Mysore, South India. RESULTS: We observed a strong association of the minor allele A at rs9939609 with type 2 diabetes (OR per allele 1.26; 95% CI 1.13-1.40; p = 3 x 10(-5)). The variant was also associated with BMI but this association appeared to be weaker (0.06 SDs; 95% CI 0.01-0.10) than the previously reported effect in Europeans (0.10 SDs; 95% CI 0.09-0.12; heterogeneity p = 0.06). Unlike in the Europeans, the association with type 2 diabetes remained significant after adjusting for BMI (OR per allele for type 2 diabetes 1.21; 95% CI 1.06-1.37; p = 4.0 x 10(-3)), and also for waist circumference and other anthropometric variables. CONCLUSIONS: Our study replicates the strong association of FTO variants with type 2 diabetes and similar to the study in North Indians Sikhs, shows that this association may not be entirely mediated through BMI. This could imply underlying differences between Indians and Europeans in the mechanisms linking body size with type 2 diabetes.

The association of common genetic variants in the APOA5, LPL and GCK genes with longitudinal changes in metabolic and cardiovascular traits.

AIMS/HYPOTHESIS: Common genetic variants influence plasma triacylglycerol, HDL-cholesterol (HDL-C) and glucose levels in cross-sectional studies. However, the longitudinal effects of these established variants have not been studied. Our aim was to examine the longitudinal associations of four such variants in the apolipoprotein A-V (APOA5), lipoprotein lipase (LPL), and glucokinase (GCK) genes with fasting glucose or lipid levels. METHODS: The individuals analysed were participants in the Busselton Health Survey (n = 4,554). Cross-sectional analyses of family data used the total association test. Longitudinal association analyses of unrelated participant data (n = 2,864) used linear mixed-effects models. RESULTS: The findings of cross-sectional association analyses replicated those of previous studies. We observed associations of the G and C alleles at the APOA5 single nucleotide polymorphisms (SNPs) rs662799 and rs3135506 with raised triacylglycerol levels (p = 0.0003 and p < 0.0001, respectively), the 447X allele at the LPL SNP rs328 with reduced triacylglycerol levels (p = 0.0004) and raised HDL-C levels (p = 0.0004), and the A allele of the GCK SNP rs1799884 with raised fasting glucose level (p = 0.015). Longitudinal association analyses showed that most of these associations did not change in the same individuals over an average follow-up time of 17.4 years, though there was some evidence that the association of the 447X allele of rs328 with raised HDL-C level significantly increased with age (p = 0.01), and that the association of the C allele of rs3135506 with raised triacylglycerol level significantly increased over time (p = 0.0007). CONCLUSIONS/INTERPRETATION: The current study suggests that the effects of established gene variants on lipid and glucose traits do not tend to alter with age during adulthood or over time.

Gene variants influencing measures of inflammation or predisposing to autoimmune and inflammatory diseases are not associated with the risk of type 2 diabetes.

AIMS/HYPOTHESIS: There are strong associations between measures of inflammation and type 2 diabetes, but the causal directions of these associations are not known. We tested the hypothesis that common gene variants known to alter circulating levels of inflammatory proteins, or known to alter autoimmune-related disease risk, influence type 2 diabetes risk. METHODS: We selected 46 variants: (1) eight variants known to alter circulating levels of inflammatory proteins, including those in the IL18, IL1RN, IL6R, MIF, PAI1 (also known as SERPINE1) and CRP genes; and (2) 38 variants known to predispose to autoimmune diseases, including type 1 diabetes. We tested the associations of these variants with type 2 diabetes using a meta-analysis of 4,107 cases and 5,187 controls from the Wellcome Trust Case Control Consortium, the Diabetes Genetics Initiative, and the Finland-United States Investigation of NIDDM studies. We followed up associated variants (p < 0.01) in a further set of 3,125 cases and 3,596 controls from the UK. RESULTS: We found no evidence that inflammatory or autoimmune disease variants are associated with type 2 diabetes (at p

A genetic link between type 2 diabetes and prostate cancer.

Epidemiological studies suggest that men with type 2 diabetes are less likely than non-diabetic men to develop prostate cancer. The cause of this association is not known. Recent genetic studies have highlighted a potential genetic link between the two diseases. Two studies have identified a version (allele) of a variant in the HNF1B (also known as TCF2) gene that predisposes to type 2 diabetes, and one of them showed that the same allele protects men from prostate cancer. Other, separate, studies have identified different variants in the JAZF1 gene, one associated with type 2 diabetes, another associated with prostate cancer. These findings are unlikely to completely explain the epidemiological association between the two diseases but they provide new insight into a possible direct causal link, rather than one that is confounded or biased in some way.

Beta cell glucose sensitivity is decreased by 39% in non-diabetic individuals carrying multiple diabetes-risk alleles compared with those with no risk alleles.

AIMS/HYPOTHESIS: Novel type 2 diabetes-susceptibility loci have been identified with evidence that individually they mediate the increased diabetes risk through altered pancreatic beta cell function. The aim of this study was to test the cumulative effects of diabetes-risk alleles on measures of beta cell function in non-diabetic individuals. METHODS: A total of 1,211 non-diabetic individuals underwent metabolic assessment including an OGTT, from which measures of beta cell function were derived. Individuals were genotyped at each of the risk loci and then classified according to the total number of risk alleles that they carried. Initial analysis focused on CDKAL1, HHEX/IDE and TCF7L2 loci, which were individually associated with a decrease in beta cell function in our cohort. Risk alleles for CDKN2A/B, SLC30A8, IGF2BP2 and KCNJ11 loci were subsequently included into the analysis. RESULTS: The diabetes-risk alleles for CDKAL1, HHEX/IDE and TCF7L2 showed an additive model of association with measures of beta cell function. Beta cell glucose sensitivity was decreased by 39% in those individuals with five or more risk alleles compared with those individuals with no risk alleles (geometric mean [SEM]: 84 [1.07] vs 137 [1.11] pmol min(-1) m(-2) (mmol/l)(-1), p = 1.51 x 10(-6)). The same was seen for the 30 min insulin response (p = 4.17 x 10(-7)). The relationship remained after adding in the other four susceptibility loci (30 min insulin response and beta cell glucose sensitivity, p < 0.001 and p = 0.003, respectively). CONCLUSIONS/INTERPRETATION: This study shows how individual type 2 diabetes-risk alleles combine in an additive manner to impact upon pancreatic beta cell function in non-diabetic individuals.