Peter Almgren

Genome-Wide Association Analysis Identifies Loci for Type 2 Diabetes and Triglyceride Levels

New strategies for prevention and treatment of type 2 diabetes (T2D) require improved insight into disease etiology. We analyzed 386,731 common single-nucleotide polymorphisms (SNPs) in 1464 patients with T2D and 1467 matched controls, each characterized for measures of glucose metabolism, lipids, obesity, and blood pressure. With collaborators (FUSION and WTCCC/UKT2D), we identified and confirmed three loci associated with T2D—in a noncoding region near CDKN2A and CDKN2B, in an intron of IGF2BP2, and an intron of CDKAL1—and replicated associations near HHEX and in SLC30A8 found by a recent whole-genome association study. We identified and confirmed association of a SNP in an intron of glucokinase regulatory protein (GCKR) with serum triglycerides. The discovery of associated variants in unsuspected genes and outside coding regions illustrates the ability of genome-wide association studies to provide potentially important clues to the pathogenesis of common diseases.

Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and ∼2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 × 10−14), CDC123-CAMK1D (P = 1.2 × 10−10), TSPAN8-LGR5 (P = 1.1 × 10−9), THADA (P = 1.1 × 10−9), ADAMTS9 (P = 1.2 × 10−8) and NOTCH2 (P = 4.1 × 10−8) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.

Clinical Risk Factors, DNA Variants, and the Development of Type 2 Diabetes

BACKGROUND Type 2 diabetes mellitus is thought to develop from an interaction between environmental and genetic factors. We examined whether clinical or genetic factors or both could predict progression to diabetes in two prospective cohorts. METHODS We genotyped 16 single-nucleotide polymorphisms (SNPs) and examined clinical factors in 16,061 Swedish and 2770 Finnish subjects. Type 2 diabetes developed in 2201 (11.7%) of these subjects during a median follow-up period of 23.5 years. We also studied the effect of genetic variants on changes in insulin secretion and action over time. RESULTS Strong predictors of diabetes were a family history of the disease, an increased body-mass index, elevated liver-enzyme levels, current smoking status, and reduced measures of insulin secretion and action. Variants in 11 genes (TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX) were significantly associated with the risk of type 2 diabetes independently of clinical risk factors; variants in 8 of these genes were associated with impaired beta-cell function. The addition of specific genetic information to clinical factors slightly improved the prediction of future diabetes, with a slight increase in the area under the receiver-operating-characteristic curve from 0.74 to 0.75; however, the magnitude of the increase was significant (P=1.0x10(-4)). The discriminative power of genetic risk factors improved with an increasing duration of follow-up, whereas that of clinical risk factors decreased. CONCLUSIONS As compared with clinical risk factors alone, common genetic variants associated with the risk of diabetes had a small effect on the ability to predict the future development of type 2 diabetes. The value of genetic factors increased with an increasing duration of follow-up.

Mechanisms by which common variants in the TCF7L2 gene increase risk of type 2 diabetes

Genetic variants in the gene encoding for transcription factor-7-like 2 (TCF7L2) have been associated with type 2 diabetes (T2D) and impaired beta cell function, but the mechanisms have remained unknown. We therefore studied prospectively the ability of common variants in TCF7L2 to predict future T2D and explored the mechanisms by which they would do this. Scandinavian subjects followed for up to 22 years were genotyped for 3 SNPs (rs7903146, rs12255372, and rs10885406) in TCF7L2, and a subset of them underwent extensive metabolic studies. Expression of TCF7L2 was related to genotype and metabolic parameters in human islets. The CT/TT genotypes of SNP rs7903146 strongly predicted future T2D in 2 independent cohorts (Swedish and Finnish). The risk T allele was associated with impaired insulin secretion, incretin effects, and enhanced rate of hepatic glucose production. TCF7L2 expression in human islets was increased 5-fold in T2D, particularly in carriers of the TT genotype. Overexpression of TCF7L2 in human islets reduced glucose-stimulated insulin secretion. In conclusion, the increased risk of T2D conferred by variants in TCF7L2 involves the enteroinsular axis, enhanced expression of the gene in islets, and impaired insulin secretion.

Novel and conventional biomarkers for prediction of incident cardiovascular events in the community.

CONTEXT Prior studies have demonstrated conflicting results regarding how much information novel biomarkers add to cardiovascular risk assessment. OBJECTIVE To evaluate the utility of contemporary biomarkers for predicting cardiovascular risk when added to conventional risk factors. DESIGN, SETTING, AND PARTICIPANTS Cohort study of 5067 participants (mean age, 58 years; 60% women) without cardiovascular disease from Malmö, Sweden, who attended a baseline examination between 1991 and 1994. Participants underwent measurement of C-reactive protein (CRP), cystatin C, lipoprotein-associated phospholipase 2, midregional proadrenomedullin (MR-proADM), midregional proatrial natriuretic peptide, and N-terminal pro-B-type natriuretic peptide (N-BNP) and underwent follow-up until 2006 using the Swedish national hospital discharge and cause-of-death registers and the Stroke in Malmö register for first cardiovascular events (myocardial infarction, stroke, coronary death). MAIN OUTCOME MEASURES Incident cardiovascular and coronary events. RESULTS During median follow-up of 12.8 years, there were 418 cardiovascular and 230 coronary events. Models with conventional risk factors had C statistics of 0.758 (95% confidence interval [CI], 0.734 to 0.781) and 0.760 (0.730 to 0.789) for cardiovascular and coronary events, respectively. Biomarkers retained in backward-elimination models were CRP and N-BNP for cardiovascular events and MR-proADM and N-BNP for coronary events, which increased the C statistic by 0.007 (P = .04) and 0.009 (P = .08), respectively. The proportion of participants reclassified was modest (8% for cardiovascular risk, 5% for coronary risk). Net reclassification improvement was nonsignificant for cardiovascular events (0.0%; 95% CI, -4.3% to 4.3%) and coronary events (4.7%; 95% CI, -0.76% to 10.1%). Greater improvements were observed in analyses restricted to intermediate-risk individuals (cardiovascular events: 7.4%; 95% CI, 0.7% to 14.1%; P = .03; coronary events: 14.6%; 95% CI, 5.0% to 24.2%; P = .003). However, correct reclassification was almost entirely confined to down-classification of individuals without events rather than up-classification of those with events. CONCLUSIONS Selected biomarkers may be used to predict future cardiovascular events, but the gains over conventional risk factors are minimal. Risk classification improved in intermediate-risk individuals, mainly through the identification of those unlikely to develop events.

Common Single Nucleotide Polymorphisms in TCF7L2 Are Reproducibly Associated With Type 2 Diabetes and Reduce the Insulin Response to Glucose in Nondiabetic Individuals

Recently, common noncoding variants in the TCF7L2 gene were strongly associated with increased risk of type 2 diabetes in samples from Iceland, Denmark, and the U.S. We genotyped 13 single nucleotide polymorphisms (SNPs) across TCF7L2 in 8,310 individuals in family-based and case-control designs from Scandinavia, Poland, and the U.S. We convincingly confirmed the previous association of TCF7L2 SNPs with the risk of type 2 diabetes (rs7903146T odds ratio 1.40 [95% CI 1.30–1.50], P = 6.74 × 10−20). In nondiabetic individuals, the risk genotypes were associated with a substantial reduction in the insulinogenic index derived from an oral glucose tolerance test (risk allele homozygotes have half the insulin response to glucose of noncarriers, P = 0.003) but not with increased insulin resistance. These results suggest that TCF7L2 variants may act through insulin secretion to increase the risk of type 2 diabetes.

The metabolic syndrome influences the risk of chronic complications in patients with Type II diabetes

Abstract.Aims/hypothesis: We examined features of the metabolic syndrome to see if they modified the risk of chronic diabetic complications in patients with Type II (non-insulin-dependent) diabetes mellitus. Methods: A total of 85 randomly selected patients with the metabolic syndrome (WHO definition) were compared with 85 Type II diabetic patients matched for age, sex, duration of diabetes, glycaemic control and without the syndrome to assess the microvascular and macrovascular complications. Results: The patients with the metabolic syndrome had a higher prevalence of cardiovascular disease (52 vs 21 %, p < 0.001), microalbuminuria or macroalbuminuria (23 vs 7 %, p = 0.003) and distal neuropathy (16 vs 6 %, p = 0.048) than patients without the syndrome. The patients with the metabolic syndrome had smaller LDL particle size (25.4 ± 1.4 vs 26.4 ± 1.1 nm; p < 0.001), which correlated with the ratio of serum triglycerides to HDL cholesterol (r = –0.64, p < 0.001). In a multiple logistic regression analysis the metabolic syndrome was associated with coronary heart disease (RR 3.84, p < 0.001) and microalbuminuria (RR 3.99, p = 0.01). Small LDL particle size was independently associated with neuropathy (RR 0.58; p = 0.04), whereas a high HbA1 c was related to neuropathy (RR 1.69, p = 0.04), retinopathy (RR 1.53, p = 0.002) and microalbuminuria (RR 1.54, p = 0.01). Conclusion/interpretation: Although chronic hyperglycaemia is the main predictor of microvascular complications in patients with Type II diabetes, this risk is modified by some of the components of the metabolic syndrome. [Diabetologia (2001) 44: 1148–1154]

The environmental determinants of diabetes in the young (TEDDY) study: Study design

Abstract:  The primary objective of this multicenter, multinational, epidemiological study is the identification of infectious agents, dietary factors, or other environmental exposures that are associated with increased risk of autoimmunity and type 1 diabetes mellitus (T1DM). Factors affecting specific phenotypic manifestations such as early age of onset or rate of progression or with protection from the development of T1DM will also be identified. The Environmental Determinants of Diabetes in the Young (TEDDY) is an observational cohort study in which newborns who are younger than 4 months and have high‐risk human leukocyte antigen alleles in the general population or are first‐degree relatives (FDRs) of patients affected with T1DM will be enrolled. Six clinical centers in the USA and Europe will screen 361 588 newborns, of which it is anticipated that 17 804 will be eligible for enrollment with just over 7800 followed. Recruitment will occur over 5 yr, with children being followed to the age of 15 yr. Identification of such factors will lead to a better understanding of disease pathogenesis and result in new strategies to prevent, delay, or reverse T1DM.

Evaluation of Common Variants in the Six Known Maturity-Onset Diabetes of the Young (MODY) Genes for Association With Type 2 Diabetes

An important question in human genetics is the extent to which genes causing monogenic forms of disease harbor common variants that may contribute to the more typical form of that disease. We aimed to comprehensively evaluate the extent to which common variation in the six known maturity-onset diabetes of the young (MODY) genes, which cause a monogenic form of type 2 diabetes, is associated with type 2 diabetes. Specifically, we determined patterns of common sequence variation in the genes encoding Gck, Ipf1, Tcf2, and NeuroD1 (MODY2 and MODY4–MODY6, respectively), selected a comprehensive set of 107 tag single nucleotide polymorphisms (SNPs) that captured common variation, and genotyped each in 4,206 patients and control subjects from Sweden, Finland, and Canada (including family-based studies and unrelated case-control subjects). All SNPs with a nominal P value <0.1 for association to type 2 diabetes in this initial screen were then genotyped in an additional 4,470 subjects from North America and Poland. Of 30 nominally significant SNPs from the initial sample, 8 achieved consistent results in the replication sample. We found the strongest effect at rs757210 in intron 2 of TCF2, with corrected P values <0.01 for an odds ratio (OR) of 1.13. This association was observed again in an independent sample of 5,891 unrelated case and control subjects and 500 families from the U.K., for an overall OR of 1.12 and a P value <10−6 in >15,000 samples. We combined these results with our previous studies on HNF4α and TCF1 and explicitly tested for gene-gene interactions among these variants and with several known type 2 diabetes susceptibility loci, and we found no genetic interactions between these six genes. We conclude that although rare variants in these six genes explain most cases of MODY, common variants in these same genes contribute very modestly, if at all, to the common form of type 2 diabetes.

Impact of an Exercise Intervention on DNA Methylation in Skeletal Muscle From First-Degree Relatives of Patients With Type 2 Diabetes

To identify epigenetic patterns, which may predispose to type 2 diabetes (T2D) due to a family history (FH) of the disease, we analyzed DNA methylation genome-wide in skeletal muscle from individuals with (FH+) or without (FH−) an FH of T2D. We found differential DNA methylation of genes in biological pathways including mitogen-activated protein kinase (MAPK), insulin, and calcium signaling (P ≤ 0.007) and of individual genes with known function in muscle, including MAPK1, MYO18B, HOXC6, and the AMP-activated protein kinase subunit PRKAB1 in skeletal muscle of FH+ compared with FH− men. We further validated our findings from FH+ men in monozygotic twin pairs discordant for T2D, and 40% of 65 analyzed genes exhibited differential DNA methylation in muscle of both FH+ men and diabetic twins. We further examined if a 6-month exercise intervention modifies the genome-wide DNA methylation pattern in skeletal muscle of the FH+ and FH− individuals. DNA methylation of genes in retinol metabolism and calcium signaling pathways (P < 3 × 10−6) and with known functions in muscle and T2D including MEF2A, RUNX1, NDUFC2, and THADA decreased after exercise. Methylation of these human promoter regions suppressed reporter gene expression in vitro. In addition, both expression and methylation of several genes, i.e., ADIPOR1, BDKRB2, and TRIB1, changed after exercise. These findings provide new insights into how genetic background and environment can alter the human epigenome.