Pathologisch-genetisch orientierte Diabetes-Reklassifizierung

Abstract Diabetes mellitus has been defined by hyperglycemia, but in addition to hyperglycemia, there are several other factors determining the clinical course and complications. We review the current classification of diabetes and recent attempts to identify new subphenotypes. Notably, there are anthropometry-pathophysiology based and genome-based subphenotyping approaches. They aim to improve the prediction of disease course and complications and could pave the way for precision medicine in the therapy of diabetes.

[1]  B. Shields,et al.  Disease progression and treatment response in data-driven subgroups of type 2 diabetes compared with models based on simple clinical features: an analysis using clinical trial data , 2019, The lancet. Diabetes & endocrinology.

[2]  Jimmy D Bell,et al.  Genome-Wide and Abdominal MRI Data Provide Evidence That a Genetically Determined Favorable Adiposity Phenotype Is Characterized by Lower Ectopic Liver Fat and Lower Risk of Type 2 Diabetes, Heart Disease, and Hypertension , 2018, Diabetes.

[3]  B. Shields,et al.  A UK nationwide prospective study of treatment change in MODY: genetic subtype and clinical characteristics predict optimal glycaemic control after discontinuing insulin and metformin , 2018, Diabetologia.

[4]  Gad Getz,et al.  Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis , 2018, PLoS medicine.

[5]  I. Brandslund,et al.  Pathophysiology‐based phenotyping in type 2 diabetes: A clinical classification tool , 2018, Diabetes/metabolism research and reviews.

[6]  Mary E. Haas,et al.  Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations , 2018, Nature Genetics.

[7]  P. Franks,et al.  Gene-lifestyle interplay in type 2 diabetes. , 2018, Current opinion in genetics & development.

[8]  E. Topol,et al.  The personal and clinical utility of polygenic risk scores , 2018, Nature Reviews Genetics.

[9]  M. Davies,et al.  Accurate diagnosis of diabetes mellitus and new paradigms of classification , 2018, Nature Reviews Endocrinology.

[10]  L. Groop,et al.  Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. , 2018, The lancet. Diabetes & endocrinology.

[11]  D. Drucker,et al.  Precision medicine in the management of type 2 diabetes. , 2018, The lancet. Diabetes & endocrinology.

[12]  E. Bonifacio,et al.  Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes: A prospective study in children , 2018, PLoS medicine.

[13]  I. König,et al.  What is precision medicine? , 2017, European Respiratory Journal.

[14]  A. Hattersley,et al.  A type 1 diabetes genetic risk score can discriminate monogenic autoimmunity with diabetes from early-onset clustering of polygenic autoimmunity with diabetes , 2018, Diabetologia.

[15]  Samuel E. Jones,et al.  Frequency and phenotype of type 1 diabetes in the first six decades of life: a cross-sectional, genetically stratified survival analysis from UK Biobank , 2017, The lancet. Diabetes & endocrinology.

[16]  Giovanni Malerba,et al.  Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes , 2017, Nature Genetics.

[17]  F. Schick,et al.  The protective effect of human renal sinus fat on glomerular cells is reversed by the hepatokine fetuin-A , 2017, Scientific Reports.

[18]  Fritz Schick,et al.  Phenotypes of prediabetes and stratification of cardiometabolic risk. , 2016, The lancet. Diabetes & endocrinology.

[19]  H. Häring.  Novel phenotypes of prediabetes? , 2016, Diabetologia.

[20]  B. Shields,et al.  A Type 1 Diabetes Genetic Risk Score Can Aid Discrimination Between Type 1 and Type 2 Diabetes in Young Adults , 2015, Diabetes Care.

[21]  Benjamin S. Glicksberg,et al.  Identification of type 2 diabetes subgroups through topological analysis of patient similarity , 2015, Science Translational Medicine.

[22]  F. Schick,et al.  A high-risk phenotype associates with reduced improvement in glycaemia during a lifestyle intervention in prediabetes , 2015, Diabetologia.

[23]  E. Archer.  The childhood obesity epidemic as a result of nongenetic evolution: the maternal resources hypothesis. , 2015, Mayo Clinic proceedings.

[24]  A. Fritsche,et al.  Phänotypen des Prädiabetes und des Typ-2-Diabetes , 2014, Deutsche Medizinische Wochenschrift.

[25]  F. Schick,et al.  Exercise-induced albuminuria is associated with perivascular renal sinus fat in individuals at increased risk of type 2 diabetes , 2012, Diabetologia.

[26]  L. Groop,et al.  Heritability and familiality of type 2 diabetes and related quantitative traits in the Botnia Study , 2011, Diabetologia.

[27]  M. Davidson.  Diagnosing Diabetes With Glucose Criteria: Worshipping a False God , 2011, Diabetes Care.

[28]  C. Kahn,et al.  Insulin signaling to the glomerular podocyte is critical for normal kidney function. , 2010, Cell metabolism.

[29]  Michael E. Miller,et al.  ACTION TO CONTROL CARDIOVASCULAR RISK IN DIABETES STUDY GROUP. EFFECTS OF INTENSIVE GLUCOSE LOWERING IN TYPE 2 DIABETES , 2010 .

[30]  D. Clayton,et al.  Genome-wide association study and meta-analysis finds over 40 loci affect risk of type 1 diabetes , 2009, Nature Genetics.

[31]  C. Forsblom,et al.  Metabolic Syndrome as a Risk Factor for Cardiovascular Disease, Mortality, and Progression of Diabetic Nephropathy in Type 1 Diabetes , 2009, Diabetes Care.

[32]  Grant D. Huang,et al.  Glucose control and vascular complications in veterans with type 2 diabetes. , 2009, The New England journal of medicine.

[33]  S. Schinner.  Intensive Blood Glucose Control and Vascular Outcomes in Patients with Type 2 Diabetes , 2009 .

[34]  M. Fowler.  Microvascular and Macrovascular Complications of Diabetes , 2008, Clinical Diabetes.

[35]  F. Schick,et al.  High Visceral Fat Mass and High Liver Fat Are Associated with Resistance to Lifestyle Intervention , 2007, Obesity.

[36]  M. Stumvoll,et al.  Genetik des Typ-2-Diabetes , 2005, Der Internist.

[37]  F. Dotta,et al.  Type 1 diabetes mellitus as a polygenic multifactorial disease: immunopathogenic mechanisms of beta-cell destruction. , 2005, Acta bio-medica : Atenei Parmensis.

[38]  J. Levy,et al.  Correct Homeostasis Model Assessment (HOMA) Evaluation Uses the Computer Program , 1998, Diabetes Care.

[39]  M. Balabolkin,et al.  [Classification of diabetes mellitus]. , 1980, Terapevticheskii arkhiv.