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Clinical Phenotyping of Newly Diagnosed Type 2 Diabetes in Yemen

Overview
Specialty Endocrinology
Date 2019 Jan 8
PMID 30613401
Citations 7
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Abstract

Objective: To identify clinical phenotypes of type 2 diabetes (T2D) among adults presenting with a first diagnosis of diabetes.

Research Design And Methods: A total of 500 consecutive patients were subject to clinical assessment and laboratory investigations. We used data-driven cluster analysis to identify phenotypes of T2D based on clinical variables and Homeostasis Model Assessment (HOMA2) of insulin sensitivity and beta-cell function estimated from paired fasting blood glucose and specific insulin levels.

Results: The cluster analysis identified three statistically different clusters: cluster 1 (high insulin resistance and high beta-cell function group), which included patients with low insulin sensitivity and high beta-cell function; cluster 2 (low insulin resistance and low beta-cell function group), which included patients with high insulin sensitivity but very low beta-cell function; and cluster 3 (high insulin resistance and low beta-cell function group), which included patients with low insulin sensitivity and low beta-cell function. Insulin sensitivity, defined as median HOMA2-S, was progressively increasing from cluster 1 (35.4) to cluster 3 (40.9), to cluster 2 (76) (p<0.001). On the contrary, beta-cell function, defined as median HOMA2-β, was progressively declining from cluster 1 (78.3) to cluster 3 (30), to cluster 2 (22.3) (p<0.001). Clinical and biomarker variables associated with insulin resistance like obesity, abdominal adiposity, fatty liver, and high serum triglycerides were mainly seen in clusters 1 and 3. The highest median hemoglobin A1c value was noted in cluster 2 (88 mmol/mol) and the lowest in cluster 1.

Conclusion: Cluster analysis of newly diagnosed T2D in adults has identified three phenotypes based on clinical variables central to the development of diabetes and on specific clinical variables of each phenotype.

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References
1.
Kohner E, Stratton I, Aldington S, Holman R, Matthews D . Relationship between the severity of retinopathy and progression to photocoagulation in patients with Type 2 diabetes mellitus in the UKPDS (UKPDS 52). Diabet Med. 2001; 18(3):178-84. DOI: 10.1046/j.1464-5491.2001.00458.x. View

2.
Wallace T, Levy J, Matthews D . Use and abuse of HOMA modeling. Diabetes Care. 2004; 27(6):1487-95. DOI: 10.2337/diacare.27.6.1487. View

3.
Weir G, Bonner-Weir S . Five stages of evolving beta-cell dysfunction during progression to diabetes. Diabetes. 2004; 53 Suppl 3:S16-21. DOI: 10.2337/diabetes.53.suppl_3.s16. View

4.
Chen H, Sullivan G, Quon M . Assessing the predictive accuracy of QUICKI as a surrogate index for insulin sensitivity using a calibration model. Diabetes. 2005; 54(7):1914-25. DOI: 10.2337/diabetes.54.7.1914. View

5.
Retnakaran R, Cull C, Thorne K, Adler A, Holman R . Risk factors for renal dysfunction in type 2 diabetes: U.K. Prospective Diabetes Study 74. Diabetes. 2006; 55(6):1832-9. DOI: 10.2337/db05-1620. View