Literature DB >> 21127150

Personalized medicine in diabetes.

Noemi Malandrino1, Robert J Smith.   

Abstract

BACKGROUND: Multiple genes that are associated with the risk of developing diabetes or the risk of diabetes complications have been identified by candidate gene analysis and genomewide scanning. These molecular markers, together with clinical data and findings from proteomics, metabolomics, pharmacogenetics, and other methods, lead to a consideration of the extent to which personalized approaches can be applied to the treatment of diabetes mellitus. CONTENT: Known genes that cause monogenic subtypes of diabetes are reviewed, and several examples are discussed in which the genotype of an individual with diabetes can direct considerations of preferred choices for glycemic therapy. The extent of characterization of polygenic determinants of type 1 and type 2 diabetes is summarized, and the potential for using this information in personalized management of glycemia and complications in diabetes is discussed. The application and current limitations of proteomic and metabolomic methods in elucidating diabetes heterogeneity is reviewed.
SUMMARY: There is established heterogeneity in the determinants of diabetes and the risk of diabetes complications. Understanding the basis of this heterogeneity provides an opportunity for personalizing prevention and treatment strategies according to individual patient clinical and molecular characteristics. There is evidence-based support for benefits from a personalized approach to diabetes care in patients with certain monogenic forms of diabetes. It is anticipated that strategies for individualized treatment decisions in the more common forms of diabetes will emerge with expanding knowledge of polygenic factors and other molecular determinants of disease.

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Year:  2010        PMID: 21127150     DOI: 10.1373/clinchem.2010.156901

Source DB:  PubMed          Journal:  Clin Chem        ISSN: 0009-9147            Impact factor:   8.327


  12 in total

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Authors:  Dietrich Rebholz-Schuhmann; Anika Oellrich; Robert Hoehndorf
Journal:  Nat Rev Genet       Date:  2012-11-14       Impact factor: 53.242

2.  Identification of type 2 diabetes subgroups through topological analysis of patient similarity.

Authors:  Li Li; Wei-Yi Cheng; Benjamin S Glicksberg; Omri Gottesman; Ronald Tamler; Rong Chen; Erwin P Bottinger; Joel T Dudley
Journal:  Sci Transl Med       Date:  2015-10-28       Impact factor: 17.956

3.  Adenosine deaminase gene variant in diabetes and obesity.

Authors:  Sepideh Borhan Dayani; Saeedeh Asgarbeik; Mojgan Asadi; Mahsa M Amoli
Journal:  J Diabetes Metab Disord       Date:  2022-01-25

4.  Application of metabolomics in traditional chinese medicine differentiation of deficiency and excess syndromes in patients with diabetes mellitus.

Authors:  Tao Wu; Ming Yang; Hua-Feng Wei; Song-Hua He; Shun-Chun Wang; Guang Ji
Journal:  Evid Based Complement Alternat Med       Date:  2012-06-13       Impact factor: 2.629

5.  Combination of Micronutrients for Bone (COMB) Study: bone density after micronutrient intervention.

Authors:  Stephen J Genuis; Thomas P Bouchard
Journal:  J Environ Public Health       Date:  2012-01-15

6.  Palatability as an addictive trigger in obesity: a changing paradigm in the past decades.

Authors:  Noemi Malandrino; Esmeralda Capristo
Journal:  Front Psychiatry       Date:  2012-01-10       Impact factor: 4.157

7.  Pathobiochemical changes in diabetic skeletal muscle as revealed by mass-spectrometry-based proteomics.

Authors:  Kay Ohlendieck
Journal:  J Nutr Metab       Date:  2012-02-29

8.  Comment on: Leeds et al. high prevalence of microvascular complications in adults with type 1 diabetes and newly diagnosed celiac disease. Diabetes Care 2011;34:2158-2163.

Authors:  Noemi Malandrino; Esmeralda Capristo
Journal:  Diabetes Care       Date:  2012-06       Impact factor: 19.112

9.  Convergence and divergence of genetic and modular networks between diabetes and breast cancer.

Authors:  Xiaoxu Zhang; Yingying Zhang; Yanan Yu; Jun Liu; Ye Yuan; Yijun Zhao; Haixia Li; Jie Wang; Zhong Wang
Journal:  J Cell Mol Med       Date:  2015-03-06       Impact factor: 5.310

Review 10.  Genomic-based tools for the risk assessment, management, and prevention of type 2 diabetes.

Authors:  Katherine A Johansen Taber; Barry D Dickinson
Journal:  Appl Clin Genet       Date:  2015-01-07
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