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.

New quality measure for SNP array based CNV detection

MOTIVATION

Only a few large systematic studies have evaluated the impact of copy number variants (CNVs) on common diseases. Several million individuals have been genotyped on single nucleotide variation arrays, which could be used for genome-wide CNVs association studies. However, CNV calls remain prone to false positives and only empirical filtering strategies exist in the literature. To overcome this issue, we defined a new quality score (QS) estimating the probability of a CNV called by PennCNV to be confirmed by other software.

RESULTS

Out-of-sample comparison showed that the correlation between the consensus CNV status and the QS is twice as high as it is for any previously proposed CNV filters. ROC curves displayed an AUC higher than 0.8 and simulations showed an increase up to 20% in statistical power when using QS in comparison to other filtering strategies. Superior performance was confirmed also for alternative consensus CNV definition and through improving known CNV-trait associations.

AVAILABILITY AND IMPLEMENTATION

http://goo.gl/T6yuFM CONTACT: zoltan.kutalik@unil.ch or aurelien@mace@unil.chSupplementary information: Supplementary data are available at Bioinformatics online.

Type 1 Diabetes Genetic Risk Score: A Novel Tool to Discriminate Monogenic and Type 1 Diabetes

Distinguishing patients with monogenic diabetes from those with type 1 diabetes (T1D) is important for correct diagnosis, treatment, and selection of patients for gene discovery studies. We assessed whether a T1D genetic risk score (T1D-GRS) generated from T1D-associated common genetic variants provides a novel way to discriminate monogenic diabetes from T1D. The T1D-GRS was highly discriminative of proven maturity-onset diabetes of young (MODY) (n = 805) and T1D (n = 1,963) (receiver operating characteristic area under the curve 0.87). A T1D-GRS of >0.280 (>50th T1D centile) was indicative of T1D (94% specificity, 50% sensitivity). We then analyzed the T1D-GRS of 242 white European patients with neonatal diabetes (NDM) who had been tested for all known NDM genes. Monogenic NDM was confirmed in 90, 59, and 8% of patients with GRS <5th T1D centile, 50-75th T1D centile, and >75th T1D centile, respectively. Applying a GRS 50th T1D centile cutoff in 48 NDM patients with no known genetic cause identified those most likely to have a novel monogenic etiology by highlighting patients with probable early-onset T1D (GRS >50th T1D centile) who were diagnosed later and had less syndromic presentation but additional autoimmune features compared with those with proven monogenic NDM. The T1D-GRS is a novel tool to improve the use of biomarkers in the discrimination of monogenic diabetes from T1D.

Improved genetic testing for monogenic diabetes using targeted next-generation sequencing

AIMS/HYPOTHESIS

Current genetic tests for diagnosing monogenic diabetes rely on selection of the appropriate gene for analysis according to the patient's phenotype. Next-generation sequencing enables the simultaneous analysis of multiple genes in a single test. Our aim was to develop a targeted next-generation sequencing assay to detect mutations in all known MODY and neonatal diabetes genes.

METHODS

We selected 29 genes in which mutations have been reported to cause neonatal diabetes, MODY, maternally inherited diabetes and deafness (MIDD) or familial partial lipodystrophy (FPLD). An exon-capture assay was designed to include coding regions and splice sites. A total of 114 patient samples were tested--32 with known mutations and 82 previously tested for MODY (n = 33) or neonatal diabetes (n = 49) but in whom a mutation had not been found. Sequence data were analysed for the presence of base substitutions, small insertions or deletions (indels) and exonic deletions or duplications.

RESULTS

In the 32 positive controls we detected all previously identified variants (34 mutations and 36 polymorphisms), including 55 base substitutions, ten small insertions or deletions and five partial/whole gene deletions/duplications. Previously unidentified mutations were found in five patients with MODY (15%) and nine with neonatal diabetes (18%). Most of these patients (12/14) had mutations in genes that had not previously been tested.

CONCLUSIONS/INTERPRETATION

Our novel targeted next-generation sequencing assay provides a highly sensitive method for simultaneous analysis of all monogenic diabetes genes. This single test can detect mutations previously identified by Sanger sequencing or multiplex ligation-dependent probe amplification dosage analysis. The increased number of genes tested led to a higher mutation detection rate.

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.

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.

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.

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.

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 <or= 0.01). The OR observed between the variant altering IL-18 levels, rs2250417, and type 2 diabetes (OR 1.00 [95% CI 0.99-1.03]), is much lower than that expected given (1) the effect of the variant on IL-18 levels (0.28 SDs per allele); and (2) estimates, based on other studies, of the correlation between IL-18 levels and type 2 diabetes risk (approximate OR 1.15 [95% CI 1.09-1.21] per 0.28 SD increase in IL-18 levels).

CONCLUSIONS/INTERPRETATION

Our study provided no evidence that variants known to alter measures of inflammation, autoimmune or inflammatory disease risk, including type 1 diabetes, alter type 2 diabetes risk.

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.

What will whole genome searches for susceptibility genes for common complex disease offer to clinical practice?

In the developed world the majority of disease results from common, but complex disorders such as diabetes, obesity and cancer. Genetic variation explains a large proportion of an individual's risk of developing these diseases; however, success in identifying the particular gene variants involved has been limited. Recent advances in high-throughput genotyping technology, and a better understanding of the genetic architecture of complex disease has led to the development of genome-wide association studies (GWA), which are providing novel and important insights into disease processes. The results from these studies could be of substantial clinical importance in the relatively near future. In this review, we present some recent, exciting findings from studies that have used the GWA approach, and discuss the clinical application of identifying disease susceptibility genes and variants.

The importance of TCF7L2

After many years of frustratingly limited success, the genetic architecture of Type 2 diabetes is finally being uncovered. Recent genome-wide association studies have identified novel genes predisposing to Type 2 diabetes, which are giving fascinating new insights into the pathophysiology of this complex disease. Of the genes so far identified by this approach, one stands out as having by far the biggest effect on disease risk. A common variant of TCF7L2, when present in two copies, is associated with an approximate 2-fold higher risk of Type 2 diabetes. This short review focuses on the TCF7L2 finding and discusses its significance for Type 2 diabetes genetic studies and for clinical practice.

The transcription factor 7-like 2 (TCF7L2) gene is associated with Type 2 diabetes in UK community-based cases, but the risk allele frequency is reduced compared with UK cases selected for genetic studies

AIMS

Common polymorphisms in the transcription factor 7-like 2 (TCF7L2) gene are strongly associated with Type 2 diabetes. Many studies include a large proportion of cases enriched for family history or young age of diagnosis and may therefore provide an overestimation of the general population risk. We aimed to compare the impact of TCF7L2 in UK community-based Type 2 diabetic subjects with that in subjects ascertained for genetic studies.

METHODS

We genotyped the TCF7L2 polymorphism rs7903146 in 1068 cases from two sources: 487 from 10 GP practices and 601 ascertained for genetic studies, and 2099 control subjects from two sources: 1099 parents from a birth cohort (population control subjects) and 300 subjects with normal fasting glucose aged > or = 45 years (community control subjects).

RESULTS

When compared with Type 2 diabetes cases ascertained for genetic studies, the risk allele frequency in community-based cases was lower (40 vs. 36%, P = 0.04), but there was no difference in risk allele frequency between community-based control and population-based control subjects (31 vs. 30%, P = 0.61). The T allele of rs7903146 increased Type 2 diabetes risk with an odds ratio (OR) of 1.32 (95% CI: 1.13-1.52; P = 0.0002) in community-based cases, but this OR was lower than the OR of cases enriched for genetic studies [1.58 (95% CI: 1.38-1.80), P = 1.4 x 10(-11)] and the combined OR of meta-analysis of 10 studies to date on rs7903146 [1.48 (95% CI: 1.41-1.54), P < 10(-20)].

CONCLUSION

Common variation in the TCF7L2 gene contributes to Type 2 diabetes risk in UK patients recruited in general practice, but the risk allele frequency may be lower than that in subjects enriched for genetic effects.

A common variant of the interleukin 6 receptor (IL-6r) gene increases IL-6r and IL-6 levels, without other inflammatory effects

Interleukin-6 (IL-6) is a key inflammatory cytokine, signalling to most tissues by binding to a soluble IL-6 receptor (sIL-6r), making a complex with gp130. We used 1273 subjects (mean age 68 years) from the InCHIANTI Italian cohort to study common variation in the IL-6r locus and associations with interleukin 6 receptor (IL-6r), IL-6, gp130 and a battery of inflammatory markers. The rs4537545 single nucleotide polymorphism (SNP) tags the functional non-synonymous Asp358Ala variant (rs8192284) in IL-6r (r(2)=0.89, n=343). Individuals homozygous for the rs4537545 SNP minor allele (frequency 40%) had a doubling of IL-6r levels (132.48 pg/ml, 95% CI 125.13-140.27) compared to the common allele homozygous group (68.31 pg/ml, 95% CI 65.35-71.41): in per allele regression models, the rs4537545 SNP accounted for 20% of the variance in sIL-6r, with P=5.1 x 10(-62). The minor allele of rs4537545 was also associated with higher circulating IL-6 levels (P=1.9 x 10(-4)). There was no association of this variant with serum levels of gp130 or with any of the studied pro- and anti-inflammatory markers. A common variant of the IL-6r gene results in major changes in IL-6r and IL-6 serum levels, but with no apparent effect on gp130 levels or on inflammatory status in the general population.

Common genetic variation in the gene encoding interleukin-1-receptor antagonist (IL-1RA) is associated with altered circulating IL-1RA levels

Interleukin-1-receptor antagonist (IL-1RA) modulates the biological activity of the proinflammatory cytokine interleukin-1 (IL-1) and could play an important role in the pathophysiology of inflammatory and metabolic traits. We genotyped seven single nucleotide polymorphisms (SNPs) that capture a large proportion of common genetic variation in the IL-1RN gene in 1256 participants from the Invecchiare in Chianti study. We identified five SNPs associated with circulating IL-1RA levels with varying degrees of significance (P-value range=0.016-4.9 x 10(-5)). We showed that this association is likely to be driven by one haplotype, most strongly tagged by rs4251961. This variant is only in weak linkage disequilibrium (r(2)=0.25) with a previously reported variable number of tandem repeats polymorphism (VNTR) in intron-2 although a second variant, rs579543, that tags the VNTR (r(2)=0.91), may also be independently associated with IL-1RA levels (P=0.03). We found suggestive evidence that the C allele at rs4251961 that lowers IL-1RA levels is associated with an increased IL-1beta (P=0.03) level and may also be associated with interferon -gamma (P=0.03), alpha-2 macroglobulin (P=0.008) and adiponectin (P=0.007) serum levels. In conclusion, common variation across the IL-1RN gene is strongly associated with IL-1RA levels.

Common variations in the ALMS1 gene do not contribute to susceptibility to type 2 diabetes in a large white UK population

AIMS/HYPOTHESIS

Alström syndrome is a rare monogenic disorder characterised by retinal dystrophy, deafness and obesity. Patients also have insulin resistance, central obesity and dyslipidaemia, thus showing similarities with type 2 diabetes. Rare mutations in the ALMS1 gene cause severe gene disruption in Alström patients; however, ALMS1 gene polymorphisms are common in the general population. The aim of our study was to determine whether common variants in ALMS1 contribute to susceptibility to type 2 diabetes in the UK population.

METHODS

Direct sequencing was performed on coding regions and intron/exon boundaries of the ALMS1 gene in 30 unrelated probands with type 2 diabetes. The linkage disequilibrium (LD; D' and r2) and haplotype structure were examined for the identified variants. The common (minor allele frequency [MAF] >5%) single-nucleotide polymorphisms tagging the common haplotypes (tagged SNPs [tSNPs]) were identified and genotyped in 1985 subjects with type 2 diabetes, 2,047 control subjects and 521 families.

RESULTS

We identified 18 variants with MAF between 6 and 38%. Three SNPs efficiently tagged three common haplotypes (rs1881245, rs3820700 and rs1320374). There was no association (all p > 0.05) between the tSNPs and type 2 diabetes in the case-control study and minor alleles of the tSNPs were not overtransmitted to probands with type 2 diabetes in the family study.

CONCLUSIONS/INTERPRETATION

Common variations in the ALMS1 gene were not associated with type 2 diabetes in a large study of a white UK population.