Karl-Fredrik Eriksson

Bio: Karl-Fredrik Eriksson is an academic researcher from Lund University. The author has contributed to research in topics: Diabetes mellitus & Impaired glucose tolerance. The author has an hindex of 38, co-authored 74 publications receiving 13021 citations. Previous affiliations of Karl-Fredrik Eriksson include University of Michigan & Malmö University.

PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes

Abstract: DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1α and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.

Prevention of type 2 (non-insulin-dependent) diabetes mellitus by diet and physical exercise. The 6-year Malmö feasibility study.

Abstract: From a previously reported 5-year screening programme of 6,956 47-49-year-old Malmo males, a series of 41 subjects with early-stage Type 2 (non-insulin-dependent) diabetes mellitus and 181 subjects with impaired glucose tolerance were selected for prospective study and to test the feasibility aspect of long-term intervention with an emphasis on life-style changes. A 5-year protocol, including an initial 6-months (randomised) pilot study, consisting of dietary treatment and/or increase of physical activity or training with annual check-ups, was completed by 90% of subjects. Body weight was reduced by 2.3-3.7% among participants, whereas values increased by 0.5-1.7% in non-intervened subjects with impaired glucose tolerance and in normal control subjects (p less than 0.0001); maximal oxygen uptake (ml.min-1.kg-1) was increased by 10-14% vs decreased by 5-9%, respectively (p less than 0.0001). Glucose tolerance was normalized in greater than 50% of subjects with impaired glucose tolerance, the accumulated incidence of diabetes was 10.6%, and more than 50% of the diabetic patients were in remission after a mean follow-up of 6 years. Blood pressure, lipids, and hyperinsulinaemia were reduced and early insulin responsiveness to glucose loading preserved. Improvement in glucose tolerance was correlated to weight reduction (r = 0.19, p less than 0.02) and increased fitness (r = 0.22, p less than 0.02). Treatment was safe, and mortality was low (in fact 33% lower than in the remainder of the cohort).(ABSTRACT TRUNCATED AT 250 WORDS)

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

Abstract: 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.

A Six Months Exercise Intervention Influences the Genome-wide DNA Methylation Pattern in Human Adipose Tissue

Abstract: Epigenetic mechanisms are implicated in gene regulation and the development of different diseases. The epigenome differs between cell types and has until now only been characterized for a few human tissues. Environmental factors potentially alter the epigenome. Here we describe the genome-wide pattern of DNA methylation in human adipose tissue from 23 healthy men, with a previous low level of physical activity, before and after a six months exercise intervention. We also investigate the differences in adipose tissue DNA methylation between 31 individuals with or without a family history of type 2 diabetes. DNA methylation was analyzed using Infinium HumanMethylation450 BeadChip, an array containing 485,577 probes covering 99% RefSeq genes. Global DNA methylation changed and 17,975 individual CpG sites in 7,663 unique genes showed altered levels of DNA methylation after the exercise intervention (q<0.05). Differential mRNA expression was present in 1/3 of gene regions with altered DNA methylation, including RALBP1, HDAC4 and NCOR2 (q<0.05). Using a luciferase assay, we could show that increased DNA methylation in vitro of the RALBP1 promoter suppressed the transcriptional activity (p = 0.03). Moreover, 18 obesity and 21 type 2 diabetes candidate genes had CpG sites with differences in adipose tissue DNA methylation in response to exercise (q<0.05), including TCF7L2 (6 CpG sites) and KCNQ1 (10 CpG sites). A simultaneous change in mRNA expression was seen for 6 of those genes. To understand if genes that exhibit differential DNA methylation and mRNA expression in human adipose tissue in vivo affect adipocyte metabolism, we silenced Hdac4 and Ncor2 respectively in 3T3-L1 adipocytes, which resulted in increased lipogenesis both in the basal and insulin stimulated state. In conclusion, exercise induces genome-wide changes in DNA methylation in human adipose tissue, potentially affecting adipocyte metabolism.

Relationship Between Testosterone Levels, Insulin Sensitivity, and Mitochondrial Function in Men

Abstract: OBJECTIVE — The goal of this study was to examine the relationship between serum testosterone levels and insulin sensitivity and mitochondrial function in men. RESEARCH DESIGN AND METHODS —A total of 60 men (mean age 60.5 ± 1.2 years) had a detailed hormonal and metabolic evaluation. Insulin sensitivity was measured using a hyperinsulinemic-euglycemic clamp. Mitochondrial function was assessed by measuring maximal aerobic capacity ( V o 2max ) and expression of oxidative phosphorylation genes in skeletal muscle. RESULTS —A total of 45% of subjects had normal glucose tolerance, 20% had impaired glucose tolerance, and 35% had type 2 diabetes. Testosterone levels were positively correlated with insulin sensitivity ( r = 0.4, P n = 10) had a BMI >25 kg/m 2 and a threefold higher prevalence of the metabolic syndrome than their eugonadal counterparts ( n = 50); this relationship held true after adjusting for age and sex hormone–binding globulin but not BMI. Testosterone levels also correlated with V o 2max ( r = 0.43, P r = 0.57, P CONCLUSIONS —These data indicate that low serum testosterone levels are associated with an adverse metabolic profile and suggest a novel unifying mechanism for the previously independent observations that low testosterone levels and impaired mitochondrial function promote insulin resistance in men.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance.

Abstract: Background Type 2 diabetes mellitus is increasingly common, primarily because of increases in the prevalence of a sedentary lifestyle and obesity. Whether type 2 diabetes can be prevented by interventions that affect the lifestyles of subjects at high risk for the disease is not known. Methods We randomly assigned 522 middle-aged, overweight subjects (172 men and 350 women; mean age, 55 years; mean body-mass index [weight in kilograms divided by the square of the height in meters], 31) with impaired glucose tolerance to either the intervention group or the control group. Each subject in the intervention group received individualized counseling aimed at reducing weight, total intake of fat, and intake of saturated fat and increasing intake of fiber and physical activity. An oral glucose-tolerance test was performed annually; the diagnosis of diabetes was confirmed by a second test. The mean duration of follow-up was 3.2 years. Results The mean (±SD) amount of weight lost between base line and the end of ye...

Standards of Medical Care in Diabetes

Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes

Abstract: DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1α and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.