الفهرس 
DedicationOnly 14 pages are availabe for public view
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Abstract
Background:Type 2 diabetes mellitus (T2DM) and metabolic syndrome are associated with decreased insulin like growth factor1 (IGF-1) and vitamin D. In contrast, high pro-neurotensin (pro-NT) levels were linked with an increased risk of T2DM and cardiovascular disease. We aimed to determine the validity of IGF-1, pro-NT and 25-hydroxyvitamin D3 (25(OH)D3) levels as predictors for T2DM complications and to examine the possible correlations of the candidate biomarkerswithT2DM laboratory markers and indices of glucose regulation.
Methods: Hundred T2DM, and 100 healthy volunteers, participated in this case-control study. The IGF-1, pro-NT and 25(OH)D3 levels were evaluated using the ELISA technique.
Results: IGF-1, pro-NT and 25(OH)D3showed significant validity and accuracy in T2DM prediction, 92%, 84.5%, and 90.5%, respectively (p=0.001) as well as accuracy in prediction of T2DM complications, 80%, 64% and 64%, respectively (p=0.05). At a value of ˂44.5 ng/ml, IGF-I had sensitivity and specificity of 92% in predicting T2DM. Moreover, it predicted complications of T2DM with 70.3%sensitivity and 85.7%specificity at a value of ˂ 29.5 ng/ml.At a value of >124 pmol/L, pro-NT showed 81% sensitivity and 88% specificity in predicting T2DM, while it predicted T2DM complications with 67.6% sensitivity and 56.0% specificity at a value of >158 pmol/L.At a value of less than 29.5 ng/ml, 25(OH)D3 showed 88% sensitivity and 93% specificity in predicting T2DM and at a value of 16.5 ng/ml, it had 78.4% sensitivity and 68.3% specificity in predicting T2DM complications.IGF-1 levels werenegatively correlatedwithFPG, PPPG, fasting insulin, HOMA-IR and pro-NT, yetpositively correlatedwith 25 (OH) D3.In addition, pro-NT level was negatively correlated25(OH)D3and positively correlatedwithglycosylated hemoglobin (HbA1C), FPG and HOMA-IR.There was a statistically significant negative correlation between 25 (OH) D3 and HbA1C and HOMA-IR.
Conclusions:IGF-1, 25(OH)D3 and pro-NT can identify T2DM patients and predict T2DM complications with substantial sensitivity and specificity.