Åke Lernmark

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially. APPROACH An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence Based Laboratory Medicine Committee of the AACC jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association. CONTENT In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A(1c) (Hb A(1c)) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of Hb A(1c). The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed. SUMMARY The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended.

A novel radioligand binding assay to determine diagnostic accuracy of isoform-specific glutamic acid decarboxylase antibodies in childhood iDDM

SummaryInsulin-dependent diabetes mellitus (IDDM) is associated with autoreactivity against GAD but the diagnostic sensitivity (positivity in disease) and specificity (negativity in health) of isoform-specific GAD antibodies have yet to be defined in assay systems suitable for screening large number of samples. One set of IDDM patient (n=10) and control (n=50) standard sera were used to develop quantitative antibody assays with in vitro synthesized recombinant 35S-methionine-labelled GAD65 and GAD67, respectively, and protein A-Sepharose to separate free from antibody-bound ligand. Binding levels were not normally distributed (p<0.0001) and therefore, the diagnostic accuracy of GAD antibodies was analysed by the ROC plots in population-based, consecutively-diagnosed, recent onset, 0–14 year-old patients (n=105), and matched, healthy control subjects (n=157). The ROC plots showed that the diagnostic sensitivity of GAD65 antibodies was 77% and the specificity 92% compared with 8% and 98%, respectively for GAD67 antibodies. In the IDDM sera, GAD65 and GAD67 antibodies were concordant in 7% (6 of 81) and GAD65 antibodies and ICA in 89% (72 of 81) without a correlation between the autoantibody levels. Autoantibodies to recombinant human islet GAD65 are specific and sensitive markers for childhood IDDM in this immunoassay with in vitro synthesized 35S-methioninelabelled recombinant GAD.

Islet-Cell-Surface Antibodies in Juvenile Diabetes Mellitus

Using an indirect immunofluorescence test on suspensions of viable, insulin-producing islet cells from rats, we found that 32 per cent (28/88) of insulin-treated patients with juvenile diabetes have islet-cell-surface antibodies in their circulation. These antibodies also occurred in four of nine children with glucose intolerance, in one of 24 healthy children and in nondiabetic children with thyroid disorders. In the diabetic children, the immunofluorescent reaction was inhibited by preadsorption of serum to islet cells but was little affected by preadsorption to rat hepatocytes or erythrocytes or to acetone powders of various rat tissues, including pancreas. These results show that organ-specific, nonspecies-specific antibodies reactive with the cell surface of the islet cells can be present in serum from diabetic children, and provide an approach to investigation of immunopathological aspects of diabetes mellitus.

Glutamate decarboxylase-, insulin-, and islet cell-antibodies and HLA typing to detect diabetes in a general population-based study of Swedish children.

Most autoimmune diabetes occurs in those without a diabetic relative, but few cases are identifiable prospectively. To model general population prediction, 491 consecutive newly diabetic children from all of Sweden were tested for autoantibodies to glutamate decarboxylase (GAD65ab), insulin (IAA), and islet cells (ICA), and for HLA-DQ genotypes by PCR; 415 matched control children were tested in parallel. GAD65ab sensitivity/specificity was 70/96%, versus 84/96% for ICA, 56/97% for IAA, 93/93% (any positive), 39/99.7% (all positive), and 41/99.7% (GAD65ab plus IAA). The latters 25% predictive value was not improved by requiring concomitant high-risk HLA genotypes. GAD65ab were associated with DQA1*0501/B1*0201 (DQ2; P = 0.007) but not DQA1*0301/B1*0302 (DQ8), and IAA with DQA1*0301/B1*0302 (DQ8; P = 0.03) but not DQA1*0501/B1*0201 (DQ2). GAD65ab were more prevalent in females than males (79 vs. 63%; P < 0.0001) but did not vary with onset age nor season. Combining the three antibody assays yielded sufficient sensitivity for screening. GADab were relatively sensitive/specific for diabetes, but even with HLA marker combinations yielded predictive values insufficient for early immunointervention in the low-prevalence general population.

Interferon Expression in the Pancreases of Patients With Type I Diabetes

We have used a reverse transcriptase–polymerase chain reaction (RT-PCR) protocol to examine the expression of cytokines in the pancreases and islets of patients with type I diabetes. We detect a significant increase in the level of expression of interferon (IFN)-α in the pancreases of the diabetic patients as compared with the control pancreases. In contrast, IFN-β was detected at comparable levels in both groups, while IFN-γ was detected in three of four control pancreases and one of four pancreases from the diabetic individuals. The IFN-α cDNAs generated by the RT-PCR were cloned and sequenced to determine which α-subtypes were being expressed. We found that the repertoire of subtypes was quite limited in any one individual (diabetic or not), although each individual was different with respect to the pattern of subtypes expressed. We also examined these pancreases for the expression of tumor necrosis factor (TNF)-α, interleukin (IL)-1α, IL-2, IL-4, and IL-6. We found no detectable expression of TNF-α or IL-2 in any pancreases, and the expression of the other cytokines was variable, with no pattern emerging from the comparison of the diabetic and nondiabetic individuals. We conclude that, of the cytokines examined, only IFN-α was significantly increased in the diabetic patients, a result that is consistent with the possibility that this cytokine is directly involved in the development of type I diabetes.

Quantitative assay using recombinant human islet glutamic acid decarboxylase (GAD65) shows that 64K autoantibody positivity at onset predicts diabetes type.

At and before onset, most insulin-dependent diabetics (IDDM) have islet GAD65 autoantibodies (GAD65Ab). Since IDDM also occurs in older patients where non-insulin-dependent diabetes is common, we studied GAD65Ab at onset to classify diabetes type. Our quantitative immunoprecipitation assay uses recombinant human islet GAD65 stably expressed in hamster fibroblasts. Electrophoretic mobility was identical to native islet GAD65. Like native antigen, recombinant GAD65 migrated as two bands during electrophoresis, but converted to one under stronger reduction. Immunoprecipitation was linear with respect to antibody or antigen concentration. In 120 population-based diabetic patients of all ages grouped by treatment at onset and after 18 mo, GAD65Ab were present in 70% on insulin (n = 37), 10% on oral agent (n = 62, P < 0.0001), 69% changing from oral agent to insulin (n = 16, P < 0.001), and 1 of 33 controls. 65% with GAD65Ab, versus 8% without, changed from oral agent to insulin (P < 0.01). The GAD65Ab quantitative index was remarkably stable, and only 2 of 32 patients changed antibody status during follow-up. Concordance between GAD65Ab and islet cell antibodies was 93%. Quantitative correlation was approximate but significant. This highly sensitive, quantitative, high capacity assay for GAD65Ab reveals treatment requirements better than clinical criteria, perhaps guiding immunomodulatory therapy.

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.

BLUEPRINT to decode the epigenetic signature written in blood

volume 30 number 3 march 2012 nature biotechnology To the Editor: Last October, scientists gathered in Amsterdam to celebrate the start of BLUEPRINT (http://www.blueprintepigenome.eu/), an EU-funded consortium that will generate epigenomic maps of at least 100 different blood cell types. With this initiative, Europe has pledged a substantial contribution to the ultimate goal of the International Human Epigenome Consortium (IHEC) to map 1,000 human epigenomes. Here, we provide a brief background to the scientific questions that prompted the formation of BLUEPRINT, summarize the overall goals of BLUEPRINT and detail the specific areas in which the consortium will focus its initial efforts and resources. In mammals, nucleated cells share the same genome but have different epigenomes depending on the cell type and many other factors, resulting in an astounding diversity in phenotypic plasticity with respect to morphology and function. This diversity is defined by cell-specific patterns of gene expression, which are controlled through regulatory sites in the genome to which transcription factors bind. In eukaryotes, access to these sites is orchestrated via chromatin, the complex of DNA, RNA and proteins that constitutes the functional platform of the genome. In contrast with DNA, chromatin is not static but highly dynamic, particularly through modifications of histones at nucleosomes and cytosines at the DNA level that together define the epigenome, the epigenetic state of the cell. Advances in new genomics technologies, particularly next-generation sequencing, allow the epigenome to be studied in a holistic fashion, leading to a better understanding of chromatin function and functional annotation of the genome. Yet little is known about how epigenetic characteristics vary between different cell types, in health and disease or among individuals. This lack of a quantitative framework for the dynamics of the epigenome and its determinants is a major hurdle for the translation of epigenetic observations into regulatory models, the identification of associations between epigenotypes and diseases, and the subsequent development of new classes of compounds for disease prevention and treatment. The task, however, is daunting as each of the several hundred cell types in the human body is expected to show specific epigenomic features that are further expected to respond to environmental inputs in time and space. The research community has realized these limitations and the need for concerted action. The IHEC was founded to coordinate large-scale international efforts toward the goal of a comprehensive human epigenome reference atlas (http://www.ihec-epigenomes. org/). The IHEC will coordinate epigenomic mapping and characterization worldwide to avoid redundant research efforts, implement high data quality standards, coordinate data storage, management and analysis, and provide free access to the epigenomes produced. The maps generated under the umbrella of the IHEC contain detailed information on DNA methylation, histone modification, nucleosome occupancy, and corresponding coding and noncoding RNA expression in different normal and diseased cell types. This will allow integration of different layers of epigenetic information for a wide variety of distinct cell types and thus provide a resource for both basic and applied research. BLUEPRINT aims to bridge the gap in our current knowledge between individual components of the epigenome and their functional dynamics through state-of-the-art analysis in a defined set of primarily human hematopoietic cells from healthy and diseased individuals. Mammalian blood formation or hematopoiesis is one of the best-studied systems of stem cell biology. Blood formation can be viewed as a hierarchical process, and classically, differentiation is defined to occur along the myeloid and lymphoid lineages. The identity of cellular intermediates and the geometry of branch points are still under intense investigation and therefore provide a paradigm for delineation of fundamental principles of cell fate determination and regulation of proliferation and lifespan, which differ considerably between different types of blood cells. BLUEPRINT will generate reference epigenomes of at least 50 specific blood cell types and their malignant counterparts and aim to provide high-quality reference epigenomes of primary cells from >60 individuals with detailed genetic and, where appropriate, medical records. To account for and quantify the impact of DNA sequence variation on epigenome differences, BLUEPRINT will work whenever possible on samples of known genetic variation, including samples from the Cambridge BioResource (Cambridge, UK), the International Cancer Genome Consortium and the British Diabetic Twin Study for disease-discordant monozygotic twin samples. The Wellcome Trust Sanger Institute (Hinxton, UK) will also provide full genomic sequencing for up to 100 samples. BLUEPRINT will harness existing proven technologies to generate reference epigenomes, including RNA-Seq for transcriptome analysis, bisulfite sequencing for methylome analysis, DNaseI-Seq for analysis of hypersensitive sites and ChIPSeq for analysis of at least six histone marks. Moreover, BLUEPRINT aims to develop new technologies to enhance high-throughput epigenome mapping, particularly when using few cells. BLUEPRINT is initially focusing on four main areas. One main goal of the project is to comprehensively analyze diverse epigenomic maps and make them available as an integrated BLUEPRINT-IHEC resource to the scientific community. Integration is envisioned for related projects within species (e.g., the 1000 Genomes Project) and between species (e.g., modENCODE) to better understand functional aspects (e.g., shared pathways) and the evolution of cell lineage development. Analysis of the BLUEPRINT data is expected to catalyze a better understanding of the relationship between epigenetic and genomic information and will form the basis for generation of new methods (e.g., epigenetic imputation) for prediction of epigenetic states from epigenomic profiles. Such prediction methods will facilitate a move toward a more quantitative knowledge and modeling of epigenetic mechanisms. As a result, such models could in the future assist in ‘reverse engineering’ of regulatory networks to repair or restore epigenetic codes that have been perturbed by disease. A second goal of BLUEPRINT is to systematically link epigenetic variation with phenotypic plasticity in health and disease. This will be attempted in three ways. First, genetic and epigenetic varation in two blood cell types from 100 healthy individuals will be analyzed. These measurements will be combined with whole-genome and transcriptome sequencing to dissect the interplay between common DNA sequence BLUEPRINT to decode the epigenetic signature written in blood CORRESPONDENCE

Activating germline mutations in STAT3 cause early-onset multi-organ autoimmune disease.

Monogenic causes of autoimmunity provide key insights into the complex regulation of the immune system. We report a new monogenic cause of autoimmunity resulting from de novo germline activating STAT3 mutations in five individuals with a spectrum of early-onset autoimmune disease, including type 1 diabetes. These findings emphasize the critical role of STAT3 in autoimmune disease and contrast with the germline inactivating STAT3 mutations that result in hyper IgE syndrome.

The Environmental Determinants of Diabetes in the Young (TEDDY) Study

The etiology of type 1 diabetes (T1D) remains unknown, but a growing body of evidence points to infectious agents and/or components of early childhood diet. The National Institutes of Health has established the TEDDY Study consortium of six clinical centers in the United States and Europe and a data coordinating center to identify environmental factors predisposing to, or protective against, islet autoimmunity and T1D. From 2004–2009, TEDDY will screen more than 360,000 newborns from both the general population and families already affected by T1D to identify an estimated 17,804 children with high‐risk HLA‐DR,DQ genotypes. Of those, 7,801 (788 first‐degree relatives and 7,013 newborns with no family history of T1D) will be enrolled in prospective follow‐up beginning before the age of 4.5 months. As of May 2008, TEDDY has screened more than 250,000 newborns and enrolled nearly 5,000 infants—approximately 70% of the final cohort. Participants are seen every 3 months up to 4 years of age, with subsequent visits every 6 months until the subject is 15 years of age. Blood samples are collected at each visit for detection of candidate infectious agents and nutritional biomarkers; monthly stool samples are collected for infectious agents. These samples are saved in a central repository. Primary endpoints include (1) appearance of one or more islet autoantibodies (to insulin, GAD65 or IA‐2) confirmed at two consecutive visits; (2) development of T1D. By age 15, an estimated 800 children will develop islet autoimmunity and 400 will progress to T1D; 67 and 27 children have already reached these endpoints.