Eero Lindholm

Common Missense Variant in the Glucokinase Regulatory Protein Gene Is Associated With Increased Plasma Triglyceride and C-Reactive Protein but Lower Fasting Glucose Concentrations

OBJECTIVE—Using the genome-wide association approach, we recently identified the glucokinase regulatory protein gene (GCKR, rs780094) region as a novel quantitative trait locus for plasma triglyceride concentration in Europeans. Here, we sought to study the association of GCKR variants with metabolic phenotypes, including measures of glucose homeostasis, to evaluate the GCKR locus in samples of non-European ancestry and to fine- map across the associated genomic interval. RESEARCH DESIGN AND METHODS—We performed association studies in 12 independent cohorts comprising >45,000 individuals representing several ancestral groups (whites from Northern and Southern Europe, whites from the U.S., African Americans from the U.S., Hispanics of Caribbean origin, and Chinese, Malays, and Asian Indians from Singapore). We conducted genetic fine-mapping across the ∼417-kb region of linkage disequilibrium spanning GCKR and 16 other genes on chromosome 2p23 by imputing untyped HapMap single nucleotide polymorphisms (SNPs) and genotyping 104 SNPs across the associated genomic interval. RESULTS—We provide comprehensive evidence that GCKR rs780094 is associated with opposite effects on fasting plasma triglyceride (Pmeta = 3 × 10−56) and glucose (Pmeta = 1 × 10−13) concentrations. In addition, we confirmed recent reports that the same SNP is associated with C-reactive protein (CRP) level (P = 5 × 10−5). Both fine-mapping approaches revealed a common missense GCKR variant (rs1260326, Pro446Leu, 34% frequency, r2 = 0.93 with rs780094) as the strongest association signal in the region. CONCLUSIONS—These findings point to a molecular mechanism in humans by which higher triglycerides and CRP can be coupled with lower plasma glucose concentrations and position GCKR in central pathways regulating both hepatic triglyceride and glucose metabolism.

Genetic Similarities Between Latent Autoimmune Diabetes in Adults, Type 1 Diabetes, and Type 2 Diabetes

OBJECTIVE—Latent autoimmune diabetes in adults (LADA) is often considered a slowly progressing subtype of type 1 diabetes, although the clinical picture more resembles type 2 diabetes. One way to improve classification is to study whether LADA shares genetic features with type 1 and/or type 2 diabetes. RESEARCH DESIGN AND METHODS—To accomplish this, we studied whether LADA shares variation in the HLA locus or INS VNTR and PTPN22 genes with type 1 diabetes or the TCF7L2 gene with type 2 diabetes in 361 LADA, 718 type 1 diabetic, and 1,676 type 2 diabetic patients, as well as 1,704 healthy control subjects from Sweden and Finland. RESULTS—LADA subjects showed, compared with type 2 diabetic patients, increased frequency of risk for the HLA-DQB1 *0201/*0302 genotype (27 vs. 6.9%; P < 1 × 10−6), with similar frequency as with type 1 diabetes (36%). In addition, LADA subjects showed higher frequencies of protective HLA-DQB1 *0602(3)/X than type 1 diabetic patients (8.1 vs. 3.2%, P = 0.003). The AA genotype of rs689, referring to the class I allele in the INS VNTR, as well as the CT/TT genotypes of rs2476601 in the PTPN22 gene, were increased both in type 1 diabetic (P = 3 × 10−14 and P = 1 × 10−10, respectively) and LADA (P = 0.001 and P = 0.002) subjects compared with control subjects. Notably, the frequency of the type 2 diabetes–associated CT/TT genotypes of rs7903146 in the TCF7L2 were increased in LADA subjects (52.8%; P = 0.03), to the same extent as in type 2 diabetic subjects (54.1%, P = 3 × 10−7), compared with control subjects (44.8%) and type 1 diabetic subjects (43.3%). CONCLUSIONS—LADA shares genetic features with both type 1 (HLA, INS VNTR, and PTPN22) and type 2 (TCF7L2) diabetes, which justifies considering LADA as an admixture of the two major types of diabetes.

Plasma Copeptin and the Risk of Diabetes Mellitus

Background— Animal studies suggest that the arginine vasopressin system may play a role in glucose metabolism, but data from humans are limited. Methods and Results— We analyzed plasma copeptin (copeptin), a stable C-terminal fragment of the arginine vasopressin prohormone. Using baseline and longitudinal data from a Swedish population-based sample (n=4742; mean age, 58 years; 60% women) and multivariable logistic regression, we examined the association of increasing quartiles of copeptin (lowest quartile as reference) with prevalent diabetes mellitus at baseline, insulin resistance (top quartile of fasting plasma insulin among nondiabetic subjects), and incident diabetes mellitus on long-term follow-up. New-onset diabetes mellitus was ascertained through 3 national and regional registers. All models were adjusted for clinical and anthropometric risk factors, cystatin C, and C-reactive protein. In cross-sectional analyses, increasing copeptin was associated with prevalent diabetes mellitus (P=0.04) and insulin resistance (P<0.001). During 12.6 years of follow-up, 174 subjects (4%) developed new-onset diabetes mellitus. The odds of developing diabetes mellitus increased across increasing quartiles of copeptin, even after additional adjustment for baseline fasting glucose and insulin (adjusted odds ratios, 1.0, 1.37, 1.79, and 2.09; P for trend=0.004). The association with incident diabetes mellitus remained significant in analyses restricted to subjects with fasting whole blood glucose <5.4 mmol/L at baseline (adjusted odds ratios, 1.0, 1.80, 1.92, and 3.48; P=0.001). Conclusions— Elevated copeptin predicts increased risk for diabetes mellitus independently of established clinical risk factors, including fasting glucose and insulin. These findings could have implications for risk assessment, novel antidiabetic treatments, and metabolic side effects from arginine vasopressin system modulation.

Power in the phenotypic extremes: a simulation study of power in discovery and replication of rare variants.

Next‐generation sequencing technologies are making it possible to study the role of rare variants in human disease. Many studies balance statistical power with cost‐effectiveness by (a) sampling from phenotypic extremes and (b) utilizing a two‐stage design. Two‐stage designs include a broad‐based discovery phase and selection of a subset of potential causal genes/variants to be further examined in independent samples. We evaluate three parameters: first, the gain in statistical power due to extreme sampling to discover causal variants; second, the informativeness of initial (Phase I) association statistics to select genes/variants for follow‐up; third, the impact of extreme and random sampling in (Phase 2) replication. We present a quantitative method to select individuals from the phenotypic extremes of a binary trait, and simulate disease association studies under a variety of sample sizes and sampling schemes. First, we find that while studies sampling from extremes have excellent power to discover rare variants, they have limited power to associate them to phenotype—suggesting high false‐negative rates for upcoming studies. Second, consistent with previous studies, we find that the effect sizes estimated in these studies are expected to be systematically larger compared with the overall population effect size; in a well‐cited lipids study, we estimate the reported effect to be twofold larger. Third, replication studies require large samples from the general population to have sufficient power; extreme sampling could reduce the required sample size as much as fourfold. Our observations offer practical guidance for the design and interpretation of studies that utilize extreme sampling. Genet. Epidemiol. 35: 236‐246, 2011.  © 2011 Wiley‐Liss, Inc.

Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables

BACKGROUND Diabetes is presently classified into two main forms, type 1 and type 2 diabetes, but type 2 diabetes in particular is highly heterogeneous. A refined classification could provide a powerful tool to individualise treatment regimens and identify individuals with increased risk of complications at diagnosis. METHODS We did data-driven cluster analysis (k-means and hierarchical clustering) in patients with newly diagnosed diabetes (n=8980) from the Swedish All New Diabetics in Scania cohort. Clusters were based on six variables (glutamate decarboxylase antibodies, age at diagnosis, BMI, HbA1c, and homoeostatic model assessment 2 estimates of β-cell function and insulin resistance), and were related to prospective data from patient records on development of complications and prescription of medication. Replication was done in three independent cohorts: the Scania Diabetes Registry (n=1466), All New Diabetics in Uppsala (n=844), and Diabetes Registry Vaasa (n=3485). Cox regression and logistic regression were used to compare time to medication, time to reaching the treatment goal, and risk of diabetic complications and genetic associations. FINDINGS We identified five replicable clusters of patients with diabetes, which had significantly different patient characteristics and risk of diabetic complications. In particular, individuals in cluster 3 (most resistant to insulin) had significantly higher risk of diabetic kidney disease than individuals in clusters 4 and 5, but had been prescribed similar diabetes treatment. Cluster 2 (insulin deficient) had the highest risk of retinopathy. In support of the clustering, genetic associations in the clusters differed from those seen in traditional type 2 diabetes. INTERPRETATION We stratified patients into five subgroups with differing disease progression and risk of diabetic complications. This new substratification might eventually help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes. FUNDING Swedish Research Council, European Research Council, Vinnova, Academy of Finland, Novo Nordisk Foundation, Scania University Hospital, Sigrid Juselius Foundation, Innovative Medicines Initiative 2 Joint Undertaking, Vasa Hospital district, Jakobstadsnejden Heart Foundation, Folkhälsan Research Foundation, Ollqvist Foundation, and Swedish Foundation for Strategic Research.

Classifying diabetes according to the new WHO clinical stages

Aims/Hypothesis: To test the usefulness of the new WHO criteria for clinical staging of diabetes in the characterization of 1977 diabetic patients. Methods: The following clinical stages were used: patients on diet and/or oral antidiabetic agents 2 years after diagnosis were considered as non-insulin requiring (NIR; n = 711) and patients who required insulin therapy after 1 year as insulin requiring for control (IRC; n = 543). Patients who because of deteriorating hyperglycemia within 1 year required insulin therapy were considered as insulin requiring for survival (IRS; n = 743). Results: The NIR patients had the highest age at onset (52 ± 12 years; mean ± SD), BMI (29.3 ± 5.2 kg/m2) and C-peptide concentrations (median 0.98 nmol/l; interquartile range 0.72–1.31 nmol/l) but the lowest frequency of GAD antibodies (5.5%) compared to the IRC and IRS groups. The IRC group had a high age at onset (49 ± 13 years), BMI (28.0 ± 4.8 kg/m2), frequency of GAD antibodies (16.8%), intermediate C-peptide concentrations (0.56 nmol/l, interquartile range 0.28–0.94), and the highest prevalence of nephropathy (31.5%) and neuropathy (68.1%). The IRS group had the lowest age at onset (23 ± 15 years), BMI (24.2 ± 3.4 kg/m2), C-peptide concentrations (0.05 nmol/l, interquartile range below detection limit 0.01) and highest frequency of GAD antibodies (44.5%). Retinopathy was more common in IRS than in IRC patients (62.1 vs. 43.9%; p < 0.001). Conclusions: The new WHO criteria seem to discriminate three distinct subgroups and thus provide a useful tool for clinical staging. The IRC patients seem to have a more severe disease than the IRS patients, which has not been clearly acknowledged in the etiological classification. However, because of the cross-sectional nature of these data, they need to be confirmed in a prospective study with defined cut-off limits for when insulin should be initiated.

Association between LTA, TNF and AGER polymorphisms and late diabetic complications.

Background Several candidate genes on the short arm of chromosome 6 including the HLA locus, TNF, LTA and AGER could be associated with late diabetic complications. The aim of our study was therefore to explore whether polymorphisms (TNF -308 G→A, LTA T60N C→A and AGER -374 T→A) in these genes alone or together (as haplotypes) increased the risk for diabetic complications. Methodology/Principal Findings The studied polymorphisms were genotyped in 742 type 1 and 2957 type 2 diabetic patients as well as in 206 non-diabetic control subjects. The Haploview program was used to analyze putative linkage disequilibrium between studied polymorphisms. The TNF, LTA and AGER polymorphisms were associated with the HLA-DQB1 risk genotypes. The AGER -374 A allele was more common in type 1 diabetic patients with than without diabetic nephropathy (31.2 vs. 28.4%, p = 0.007). In a logistic regression analysis, the LTA but not the AGER polymorphism was associated with diabetic nephropathy (OR 2.55[1.11–5.86], p = 0.03). The AGER -374 A allele was associated with increased risk of sight threatening retinopathy in type 2 diabetic patients (1.65[1.11–2.45], p = 0.01) and also with increased risk for macrovascular disease in type 1 diabetic patients (OR 2.05[1.19–3.54], p = 0.01), but with decreased risk for macrovascular disease in type 2 diabetic patients (OR 0.66[0.49–0.90], p = 0.009). The TNF A allele was associated with increased risk for macrovascular complications in type 2 (OR 1.53 [1.04–2.25], p = 0.03, but not in type 1 diabetic patients. Conclusions/Significance The association between diabetic complications and LTA, TNF and AGER polymorphisms is complex, with partly different alleles conferring susceptibility in type 1 and type 2 diabetic patients. We can not exclude the possibility that the genes are part of a large haplotype block that also includes HLA-DQB1 risk genotypes.

The −374 T/A polymorphism in the gene encoding RAGE is associated with diabetic nephropathy and retinopathy in type 1 diabetic patients

Aims/hypothesisThe receptor for AGE (RAGE) is considered to be mainly an intracellular signal-transducer or pro-inflammatory peptide of possible importance for inflammation and autoimmune diseases. Our aim was to study whether the −374 T/A polymorphism in the gene encoding RAGE (AGER) is associated with diabetes type and presence of diabetic complications.MethodsThe AGER −374 T/A polymorphism was genotyped in 867 type 1 diabetic patients, 2,467 type 2 diabetic patients and 205 non-diabetic control subjects of Scandinavian origin.ResultsAGER polymorphism was related to different HLA-DQB1 genotypes and the presence of diabetic complications. Type 1 diabetic patients had a higher frequency of the AGER −374 A/A or T/A genotypes than type 2 diabetic patients (51.1 vs 44.9%, p=0.002) and control subjects (51.1 vs 47.6%, p=0.0006). The RAGE −374 T/A polymorphism was associated with HLA-DQB1 genotypes; patients with HLA risk genotypes had a higher frequency of the A/A or T/A genotypes than patients with other HLA-DQB1 genotypes (60.3 vs 40.3%, p<0.000001). In type 1 diabetic patients, the frequency of the A/A or T/A genotypes was higher in patients with diabetic nephropathy than without (61.1 vs 46.8%, p=0.006) and with sight-threatening retinopathy than without (56.1 vs 47.6%, p=0.03). In type 2 diabetic patients with HbA1c values below the median, the T/T genotype was more frequent in patients with diabetic nephropathy than without (54.3 vs 38.2%, p=0.02).Conclusions/interpretationOur results show an association between the AGER −374 T/A polymorphism and type 1 diabetes. This association was HLA-DQB1-dependent. The polymorphism was associated with diabetic nephropathy in both type 1 and type 2 diabetes, in an HbA1c-dependent manner in the latter group, and also with sight-threatening retinopathy in type 1 diabetic patients.

Genome-wide analysis of DNA methylation in subjects with type 1 diabetes identifies epigenetic modifications associated with proliferative diabetic retinopathy

BackgroundEpigenetic variation has been linked to several human diseases. Proliferative diabetic retinopathy (PDR) is a major cause of vision loss in subjects with diabetes. However, studies examining the association between PDR and the genome-wide DNA methylation pattern are lacking. Our aim was to identify epigenetic modifications that associate with and predict PDR in subjects with type 1 diabetes (T1D).MethodsDNA methylation was analyzed genome-wide in 485,577 sites in blood from cases with PDR (n = 28), controls (n = 30), and in a prospective cohort (n = 7). False discovery rate analysis was used to correct the data for multiple testing. Study participants with T1D diagnosed before 30 years of age and insulin treatment within 1 year from diagnosis were selected based on 1) subjects classified as having PDR (cases) and 2) subjects with T1D who had had diabetes for at least 10 years when blood DNA was sampled and classified as having no/mild diabetic retinopathy also after an 8.7-year follow-up (controls). DNA methylation was also analyzed in a prospective cohort including seven subjects with T1D who had no/mild diabetic retinopathy when blood samples were taken, but who developed PDR within 6.3 years (converters). The retinopathy level was classified by fundus photography.ResultsWe identified differential DNA methylation of 349 CpG sites representing 233 unique genes including TNF, CHI3L1 (also known as YKL-40), CHN2, GIPR, GLRA1, GPX1, AHRR, and BCOR in cases with PDR compared with controls. The majority of these sites (79 %) showed decreased DNA methylation in cases with PDR. The Natural Killer cell-mediated cytotoxicity pathway was found to be significantly (P = 0.006) enriched among differentially methylated genes in cases with PDR. We also identified differential DNA methylation of 28 CpG sites representing 17 genes (e.g. AHRR, GIPR, GLRA1, and BCOR) with P <0.05 in the prospective cohort, which is more than expected by chance (P = 0.0096).ConclusionsSubjects with T1D and PDR exhibit altered DNA methylation patterns in blood. Some of these epigenetic changes may predict the development of PDR, suggesting that DNA methylation may be used as a prospective marker of PDR.

Common variants in CNDP1 and CNDP2, and risk of nephropathy in type 2 diabetes.

Aims/hypothesisSeveral genome-wide linkage studies have shown an association between diabetic nephropathy and a locus on chromosome 18q harbouring two carnosinase genes, CNDP1 and CNDP2. Carnosinase degrades carnosine (β-alanyl-l-histidine), which has been ascribed a renal protective effect as a scavenger of reactive oxygen species. We investigated the putative associations of genetic variants in CNDP1 and CNDP2 with diabetic nephropathy (defined either as micro- or macroalbuminuria) and estimated GFR in type 2 diabetic patients from Sweden.MethodsWe genotyped nine single nucleotide polymorphisms (SNPs) and one trinucleotide repeat polymorphism (D18S880, five to seven leucine repeats) in CNDP1 and CNDP2 in a case–control set-up including 4,888 unrelated type 2 diabetic patients (with and without nephropathy) from Sweden (Scania Diabetes Registry).ResultsTwo SNPs, rs2346061 in CNDP1 and rs7577 in CNDP2, were associated with an increased risk of diabetic nephropathy (rs2346061 p = 5.07 × 10−4; rs7577 p = 0.021). The latter was also associated with estimated GFR (β = −0.037, p = 0.014), particularly in women. A haplotype including these SNPs (C-C-G) was associated with a threefold increased risk of diabetic nephropathy (OR 2.98, 95% CI 2.43–3.67, p < 0.0001).Conclusions/interpretationThese data suggest that common variants in CNDP1 and CNDP2 play a role in susceptibility to kidney disease in patients with type 2 diabetes.