ABSTRACT
Background: Type II diabetes is known as one of the most important, prevalent, and expensive diseases of mankind. Late diagnosis and subsequent delayed initiation of treatment or surveillance of patients create a variety of problems for affected individuals. This has raised increasing concerns for public health authorities throughout the world. In the current study, we aimed to find a new approach for early identification of high-risk individuals at initial months of their life. This allows us to take preventive measures as early as possible
Materials and Methods: In our study, 102 infants - from one to six months - were selected and placed in two case and control groups. The case group contained 52 babies with at least one of their parents identified as a type II diabetic patient. The control group comprised 50 babies with no family history of type II diabetes in paternal and maternal first-degree relatives. Afterwards, the expression level of insulin gene was analyzed in white blood cells of both groups. Information related to infants - referred to outpatient and inpatient wards of three main pediatric hospitals placed in Tehran - and their parents were collected through questionnaires within a two-year period. The study inclusion criteria for infants were confirmed type II diabetes in at least one of their parents, the absence of any metabolic disorder, and the absence of any disturbing vital signs. After drawing 2 ml of babies' peripheral blood, total RNA of white blood cells [WBC] was extracted, and used for cDNA synthesis. Real-Time PCR was then applied to quantitatively evaluate the expression levels of insulin gene. The results of Real-Time PCR were statistically analyzed by non-parametric tests of Mann-Whitney and Kruskal-Wallis
Results: The expression of insulin gene was observed in white blood cells of all samples. However, there was a significant difference in expression levels between case and control groups [p<0.05]. There was a statistically significant difference in mean levels of gene expression among babies with diabetic mother, and healthy groups [RQ=0.5, P-value=0.002], but this value wasn't significant for babies with diabetic father [RQ=0.78, P>0.05]
Conclusion: Numerous genes contribute to the development of diabetes and novel disease-causing genes are increasingly being discovered. Identification of disease-prone individuals through examining merely one underlying gene is complicated and challenging. Interestingly, all of these abnormally functioning genes finally manifest themselves in the altered expression levels of insulin gene. The expression status of insulin gene in WBCs could be suggested as a useful approach for identification of individuals at high risk for developing diabetes. This paves the way for taking appropriate measures at infancy period in order to prevent the disease as well as inhibit its various side effects in the following years of patient's life
ABSTRACT
Mental disorders may lead to several complications in adolescents' people whose compensation is very difficult and sometime impossible. They are prone to emotional problems. Therefore, knowing prevalence of diseases and valid statistical technique is necessary to plan for prevention and control of diseases. In this cross-sectional study; direct, synthetic, and post-stratified estimation as small area methods were used to compute mental disorder symptoms [MDS] prevalence with county-level reference among adolescents in south of Iran. We conducted Mental Health Study data [MHS] conducted in Bushehr Province, southern Iran in 2005 for individual-level classification of MDS [n=2584]. Students were in grade 9, 10 and 11, and enrolled with complete satisfaction. The synthetic method was superior to the direct and post-stratified technique with respect to discrepancy statistics such as MSE and width 95% confidence interval [MSEs[synthetic]=0.001, MSEs[post-stratified]=0.010, MSEs[direct]=0.100]. In addition, the width range of 95% confidence intervals for all county estimates was 9.7% to 65.3% based on in direct methods. Besides, the width range of 95% confidence intervals for all county estimates under post-stratified and synthetic method was 16.7% to 62.2% and 11.8%-25.1%, respectively. Hence, we could categorize prevalence of mental disorder symptoms in Bushehr's counties into five categories based-on synthetic methods. Maximum and minimum prevalence belongs to Geneveh [0.403] and Dashty [0.398] counties, respectively. The MHS cannot be used as a valid source of county-level mental health prevalence data and the small-area method such synthetic method should be used to estimate prevalence of mental disorder symptoms in county-level. Furthermore, the synthetic method improved MDS prevalence more than direct and post-stratified methods