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Aims/hypothesis: Use of genetic risk scores (GRS) may help to distinguish between type 1 diabetes and type 2 diabetes, but less is known about whether GRS are associated with disease severity or progression after diagnosis. Therefore, we tested whether GRS are associated with residual beta cell function and glycaemic control in individuals with type 1 diabetes., Methods: Immunochip arrays and TOPMed were used to genotype a cross-sectional cohort (n=479, age 41.7 ± 14.9 years, duration of diabetes 16.0 years [IQR 6.0-29.0], HbA 1c 55.6 ± 12.2 mmol/mol). Several GRS, which were originally developed to assess genetic risk of type 1 diabetes (GRS-1, GRS-2) and type 2 diabetes (GRS-T2D), were calculated. GRS-C1 and GRS-C2 were based on SNPs that have previously been shown to be associated with residual beta cell function. Regression models were used to investigate the association between GRS and residual beta cell function, assessed using the urinary C-peptide/creatinine ratio, and the association between GRS and continuous glucose monitor metrics., Results: Higher GRS-1 and higher GRS-2 both showed a significant association with undetectable UCPCR (OR 0.78; 95% CI 0.69, 0.89 and OR 0.84: 95% CI 0.75, 0.93, respectively), which were attenuated after correction for sex and age of onset (GRS-2) and disease duration (GRS-1). Higher GRS-C2 was associated with detectable urinary C-peptide/creatinine ratio (≥0.01 nmol/mmol) after correction for sex and age of onset (OR 6.95; 95% CI 1.19, 40.75). A higher GRS-T2D was associated with less time below range (TBR) (OR for TBR<4% 1.41; 95% CI 1.01 to 1.96) and lower glucose coefficient of variance (β -1.53; 95% CI -2.76, -0.29)., Conclusions/interpretation: Diabetes-related GRS are associated with residual beta cell function in individuals with type 1 diabetes. These findings suggest some genetic contribution to preservation of beta cell function., (© 2024. The Author(s).)

Iterative advances in understanding of the genetics of type 1 diabetes have identified >70 genetic regions associated with risk of the disease, including strong associations across the HLA class II region that account for >50% of heritability. The increased availability of genetic data combined with the decreased costs of generating these data, have facilitated the development of polygenic scores that aggregate risk variants from associated loci into a single number: either a genetic risk score (GRS) or a polygenic risk score (PRS). PRSs incorporate the risk of many possibly correlated variants from across the genome, even if they do not reach genome-wide significance, whereas GRSs estimate the cumulative contribution of a smaller subset of genetic variants that reach genome-wide significance. Type 1 diabetes GRSs have utility in diabetes classification, aiding discrimination between type 1 diabetes, type 2 diabetes and MODY. Type 1 diabetes GRSs are also being used in newborn screening studies to identify infants at risk of future presentation of the disease. Most early studies of type 1 diabetes genetics have been conducted in European ancestry populations, but, to develop accurate GRSs across diverse ancestries, large case-control cohorts from non-European populations are still needed. The current barriers to GRS implementation within healthcare are mainly related to a lack of guidance and knowledge on integration with other biomarkers and clinical variables. Once these limitations are addressed, there is huge potential for 'test and treat' approaches to be used to tailor care for individuals with type 1 diabetes., (© 2023. The Author(s).)

Aims/hypothesis: The reason for the observed lower rate of islet autoantibody positivity in clinician-diagnosed adult-onset vs childhood-onset type 1 diabetes is not known. We aimed to explore this by assessing the genetic risk of type 1 diabetes in autoantibody-negative and -positive children and adults., Methods: We analysed GAD autoantibodies, insulinoma-2 antigen autoantibodies and zinc transporter-8 autoantibodies (ZnT8A) and measured type 1 diabetes genetic risk by genotyping 30 type 1 diabetes-associated variants at diagnosis in 1814 individuals with clinician-diagnosed type 1 diabetes (1112 adult-onset, 702 childhood-onset). We compared the overall type 1 diabetes genetic risk score (T1DGRS) and non-HLA and HLA (DR3-DQ2, DR4-DQ8 and DR15-DQ6) components with autoantibody status in those with adult-onset and childhood-onset diabetes. We also measured the T1DGRS in 1924 individuals with type 2 diabetes from the Wellcome Trust Case Control Consortium to represent non-autoimmune diabetes control participants., Results: The T1DGRS was similar in autoantibody-negative and autoantibody-positive clinician-diagnosed childhood-onset type 1 diabetes (mean [SD] 0.274 [0.034] vs 0.277 [0.026], p=0.4). In contrast, the T1DGRS in autoantibody-negative adult-onset type 1 diabetes was lower than that in autoantibody-positive adult-onset type 1 diabetes (mean [SD] 0.243 [0.036] vs 0.271 [0.026], p<0.0001) but higher than that in type 2 diabetes (mean [SD] 0.229 [0.034], p<0.0001). Autoantibody-negative adults were more likely to have the more protective HLA DR15-DQ6 genotype (15% vs 3%, p<0.0001), were less likely to have the high-risk HLA DR3-DQ2/DR4-DQ8 genotype (6% vs 19%, p<0.0001) and had a lower non-HLA T1DGRS (p<0.0001) than autoantibody-positive adults. In contrast to children, autoantibody-negative adults were more likely to be male (75% vs 59%), had a higher BMI (27 vs 24 kg/m 2 ) and were less likely to have other autoimmune conditions (2% vs 10%) than autoantibody-positive adults (all p<0.0001). In both adults and children, type 1 diabetes genetic risk was unaffected by the number of autoantibodies (p>0.3). These findings, along with the identification of seven misclassified adults with monogenic diabetes among autoantibody-negative adults and the results of a sensitivity analysis with and without measurement of ZnT8A, suggest that the intermediate type 1 diabetes genetic risk in autoantibody-negative adults is more likely to be explained by the inclusion of misclassified non-autoimmune diabetes (estimated to represent 67% of all antibody-negative adults, 95% CI 61%, 73%) than by the presence of unmeasured autoantibodies or by a discrete form of diabetes. When these estimated individuals with non-autoimmune diabetes were adjusted for, the prevalence of autoantibody positivity in adult-onset type 1 diabetes was similar to that in children (93% vs 91%, p=0.4)., Conclusions/interpretation: The inclusion of non-autoimmune diabetes is the most likely explanation for the observed lower rate of autoantibody positivity in clinician-diagnosed adult-onset type 1 diabetes. Our data support the utility of islet autoantibody measurement in clinician-suspected adult-onset type 1 diabetes in routine clinical practice., (© 2022. The Author(s).)

Aims/hypothesis: Current clinical guidelines for childhood-onset monogenic diabetes outside infancy are mainly focused on identifying and testing for dominantly inherited, predominantly MODY genes. There are no systematic studies of the recessively inherited causes of monogenic diabetes that are likely to be more common in populations with high rates of consanguinity. We aimed to determine the contribution of recessive causes of monogenic diabetes in paediatric diabetes clinics and to identify clinical criteria by which to select individuals for recessive monogenic diabetes testing., Methods: We conducted a cross-sectional study of 1093 children from seven paediatric diabetes clinics across Turkey (a population with high rates of consanguinity). We undertook genetic testing of 50 known dominant and recessive causes of monogenic diabetes for 236 children at low risk of type 1 diabetes. As a comparison, we used monogenic diabetes cases from UK paediatric diabetes clinics (a population with low rates of consanguinity)., Results: Thirty-four children in the Turkish cohort had monogenic diabetes, equating to a minimal prevalence of 3.1%, similar to that in the UK cohort (p = 0.40). Forty-one per cent (14/34) had autosomal recessive causes in contrast to 1.6% (2/122) in the UK monogenic diabetes cohort (p < 0.0001). All conventional criteria for identifying monogenic diabetes (parental diabetes, not requiring insulin treatment, HbA 1c  ≤ 58 mmol/mol [≤7.5%] and a composite clinical probability of MODY >10%) assisted the identification of the dominant (all p ≤ 0.0003) but not recessive cases (all p ≥ 0.2) in Turkey. The presence of certain non-autoimmune extra-pancreatic features greatly assisted the identification of recessive (p < 0.0001, OR 66.9) but not dominant cases., Conclusions/interpretation: Recessively inherited mutations are a common cause of monogenic diabetes in populations with high rates of consanguinity. Present MODY-focused genetic testing strategies do not identify affected individuals. To detect all cases of monogenic paediatric diabetes, it is crucial that recessive genes are included in genetic panels and that children are selected for testing if they have certain non-autoimmune extra-pancreatic features in addition to current criteria., (© 2021. The Author(s).)

Aims/hypothesis: Among white European children developing type 1 diabetes, the otherwise common HLA haplotype DR15-DQ6 is rare, and highly protective. Adult-onset type 1 diabetes is now known to represent more overall cases than childhood onset, but it is not known whether DR15-DQ6 is protective in older-adult-onset type 1 diabetes. We sought to quantify DR15-DQ6 protection against type 1 diabetes as age of onset increased., Methods: In two independent cohorts we assessed the proportion of type 1 diabetes cases presenting through the first 50 years of life with DR15-DQ6, compared with population controls. In the After Diabetes Diagnosis Research Support System-2 (ADDRESS-2) cohort (n = 1458) clinician-diagnosed type 1 diabetes was confirmed by positivity for one or more islet-specific autoantibodies. In UK Biobank (n = 2502), we estimated type 1 diabetes incidence rates relative to baseline HLA risk for each HLA group using Poisson regression. Analyses were restricted to white Europeans and were performed in three groups according to age at type 1 diabetes onset: 0-18 years, 19-30 years and 31-50 years., Results: DR15-DQ6 was protective against type 1 diabetes through to age 50 years (OR < 1 for each age group, all p < 0.001). The following ORs for type 1 diabetes, relative to a neutral HLA genotype, were observed in ADDRESS-2: age 5-18 years OR 0.16 (95% CI 0.08, 0.31); age 19-30 years OR 0.10 (0.04, 0.23); and age 31-50 years OR 0.37 (0.21, 0.68). DR15-DQ6 also remained highly protective at all ages in UK Biobank. Without DR15-DQ6, the presence of major type 1 diabetes high-risk haplotype (either DR3-DQ2 or DR4-DQ8) was associated with increased risk of type 1 diabetes., Conclusions/interpretation: HLA DR15-DQ6 confers dominant protection from type 1 diabetes across the first five decades of life., (© 2021. The Author(s).)

Aims/hypothesis: Late-onset type 1 diabetes can be difficult to identify. Measurement of endogenous insulin secretion using C-peptide provides a gold standard classification of diabetes type in longstanding diabetes that closely relates to treatment requirements. We aimed to determine the prevalence and characteristics of type 1 diabetes defined by severe endogenous insulin deficiency after age 30 and assess whether these individuals are identified and managed as having type 1 diabetes in clinical practice., Methods: We assessed the characteristics of type 1 diabetes defined by rapid insulin requirement (within 3 years of diagnosis) and severe endogenous insulin deficiency (non-fasting C-peptide <200 pmol/l) in 583 participants with insulin-treated diabetes, diagnosed after age 30, from the Diabetes Alliance for Research in England (DARE) population cohort. We compared characteristics with participants with retained endogenous insulin secretion (>600 pmol/l) and 220 participants with severe insulin deficiency who were diagnosed under age 30., Results: Twenty-one per cent of participants with insulin-treated diabetes who were diagnosed after age 30 met the study criteria for type 1 diabetes. Of these participants, 38% did not receive insulin at diagnosis, of whom 47% self-reported type 2 diabetes. Rapid insulin requirement was highly predictive of severe endogenous insulin deficiency: 85% required insulin within 1 year of diagnosis, and 47% of all those initially treated without insulin who progressed to insulin treatment within 3 years of diagnosis had severe endogenous insulin deficiency. Participants with late-onset type 1 diabetes defined by development of severe insulin deficiency had similar clinical characteristics to those with young-onset type 1 diabetes. However, those with later onset type 1 diabetes had a modestly lower type 1 diabetes genetic risk score (0.268 vs 0.279; p < 0.001 [expected type 2 diabetes population median, 0.231]), a higher islet autoantibody prevalence (GAD-, islet antigen 2 [IA2]- or zinc transporter protein 8 [ZnT8]-positive) of 78% at 13 years vs 62% at 26 years of diabetes duration; (p = 0.02), and were less likely to identify as having type 1 diabetes (79% vs 100%; p < 0.001) vs those with young-onset disease., Conclusions/interpretation: Type 1 diabetes diagnosed over 30 years of age, defined by severe insulin deficiency, has similar clinical and biological characteristics to that occurring at younger ages, but is frequently not identified. Clinicians should be aware that patients progressing to insulin within 3 years of diagnosis have a high likelihood of type 1 diabetes, regardless of initial diagnosis.

Aims/hypothesis: The aim of this study was to identify genetic variants associated with beta cell function in type 1 diabetes, as measured by serum C-peptide levels, through meta-genome-wide association studies (meta-GWAS)., Methods: We performed a meta-GWAS to combine the results from five studies in type 1 diabetes with cross-sectionally measured stimulated, fasting or random C-peptide levels, including 3479 European participants. The p values across studies were combined, taking into account sample size and direction of effect. We also performed separate meta-GWAS for stimulated (n = 1303), fasting (n = 2019) and random (n = 1497) C-peptide levels., Results: In the meta-GWAS for stimulated/fasting/random C-peptide levels, a SNP on chromosome 1, rs559047 (Chr1:238753916, T>A, minor allele frequency [MAF] 0.24-0.26), was associated with C-peptide (p = 4.13 × 10 -8 ), meeting the genome-wide significance threshold (p < 5 × 10 -8 ). In the same meta-GWAS, a locus in the MHC region (rs9260151) was close to the genome-wide significance threshold (Chr6:29911030, C>T, MAF 0.07-0.10, p = 8.43 × 10 -8 ). In the stimulated C-peptide meta-GWAS, rs61211515 (Chr6:30100975, T/-, MAF 0.17-0.19) in the MHC region was associated with stimulated C-peptide (β [SE] = - 0.39 [0.07], p = 9.72 × 10 -8 ). rs61211515 was also associated with the rate of stimulated C-peptide decline over time in a subset of individuals (n = 258) with annual repeated measures for up to 6 years (p = 0.02). In the meta-GWAS of random C-peptide, another MHC region, SNP rs3135002 (Chr6:32668439, C>A, MAF 0.02-0.06), was associated with C-peptide (p = 3.49 × 10 -8 ). Conditional analyses suggested that the three identified variants in the MHC region were independent of each other. rs9260151 and rs3135002 have been associated with type 1 diabetes, whereas rs559047 and rs61211515 have not been associated with a risk of developing type 1 diabetes., Conclusions/interpretation: We identified a locus on chromosome 1 and multiple variants in the MHC region, at least some of which were distinct from type 1 diabetes risk loci, that were associated with C-peptide, suggesting partly non-overlapping mechanisms for the development and progression of type 1 diabetes. These associations need to be validated in independent populations. Further investigations could provide insights into mechanisms of beta cell loss and opportunities to preserve beta cell function.

Aims/hypothesis: Genome-wide association (GWA) studies have identified hundreds of common genetic variants associated with obesity and type 2 diabetes. These studies have usually focused on additive association tests. Identifying deviations from additivity may provide new biological insights and explain some of the missing heritability for these diseases., Methods: We performed a GWA study using a dominance deviation model for BMI, obesity (29,925 cases) and type 2 diabetes (4,040 cases) in 120,286 individuals of British ancestry from the UK Biobank study. We also investigated whether single nucleotide polymorphisms previously shown to be associated with these traits showed any enrichment for departures from additivity., Results: Known obesity-associated variants in FTO showed strong evidence of deviation from additivity (p DOMDEV = 3 × 10(-5)) through a recessive effect of the allele associated with higher BMI. The average BMI of individuals carrying zero, one or two BMI-raising alleles was 27.27 (95% CI 27.22, 27.31) kg/m(2), 27.54 (95% CI 27.50, 27.58) kg/m(2) and 28.07 (95% CI 28.00, 28.14) kg/m(2), respectively. A similar effect was observed in 105,643 individuals from the GIANT Consortium (p DOMDEV = 0.003; meta-analysis p DOMDEV = 1 × 10(-7)). For type 2 diabetes, we detected a recessive effect (p DOMDEV = 5 × 10(-4)) at CDKAL1. Relative to homozygous non-risk allele carriers, homozygous risk allele carriers had an OR of 1.48 (95% CI 1.32, 1.65), while the heterozygous group had an OR of 1.06 (95% CI 0.99, 1.14), a result consistent with that of a previous study. We did not identify any novel associations at genome-wide significance., Conclusions/interpretation: Although we found no evidence of widespread non-additive genetic effects contributing to obesity and type 2 diabetes risk, we did find robust examples of recessive effects at the FTO and CDKAL1 loci., Access to Research Materials: Summary statistics are available at www.t2diabetesgenes.org and by request (a.r.wood@exeter.ac.uk). All underlying data are available on application from the UK Biobank.

Aims/hypothesis: Intronic single nucleotide polymorphisms (SNPs) in the CDKAL1 gene are associated with risk of developing type 2 diabetes. A strong correlation between risk alleles and lower levels of the non-coding RNA, CDKAL1-v1, has recently been reported in whole blood extracted from Japanese individuals. We sought to replicate this association in two independent cohorts: one using whole blood from white UK-resident individuals, and one using a collection of human pancreatic islets, a more relevant tissue type to study with respect to the aetiology of diabetes., Methods: Levels of CDKAL1-v1 were measured by real-time PCR using RNA extracted from human whole blood (n = 70) and human pancreatic islets (n = 48). Expression with respect to genotype was then determined., Results: In a simple linear regression model, expression of CDKAL1-v1 was associated with the lead type 2 diabetes-associated SNP, rs7756992, in whole blood and islets. However, these associations were abolished or substantially reduced in multiple regression models taking into account rs9366357 genotype: a moderately linked SNP explaining a much larger amount of the variation in CDKAL1-v1 levels, but not strongly associated with risk of type 2 diabetes., Conclusions/interpretation: Contrary to previous findings, we provide evidence against a role for dysregulated expression of CDKAL1-v1 in mediating the association between intronic SNPs in CDKAL1 and susceptibility to type 2 diabetes. The results of this study illustrate how caution should be exercised when inferring causality from an association between disease-risk genotype and non-coding RNA expression.

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.

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.

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.

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.

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.

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.

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

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.

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.