Browsing by Author "Ortega Contreras, Bernel Ignacio"

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    Determinación del polimorfismo RS9939609 de FTO, como factor de riesgo de Diabetes mellitus gestacional.
    (Universidad de Concepción., 2021) Ortega Contreras, Bernel Ignacio; Guzmán Gutiérrez, Enrique Alberto; Sánchez Rubio, Andrea Alejandra
    La Diabetes Mellitus Gestacional (DMG) es una patología caracterizada por la intolerancia a la glucosa durante el embarazo, que puede generar complicaciones materno-fetales y a largo plazo en ambos. El polimorfismo rs9939609 del gen FTO podría generar predisposición genética a desarrollar DMG, dada su asociación con el índice de masa corporal, factor de riesgo para dicha patología. El objetivo de esta investigación fue determinar si el alelo de riesgo “A”, del polimorfismo rs9939609 en el gen FTO aumenta el riesgo a desarrollar DMG, en mujeres embarazadas de la ciudad de Concepción. Se reclutaron 81 pacientes embarazadas, 13 con DMG y 68 con Tolerancia Normal a la Glucosa (TNG), provenientes de CESFAMs de Concepción. Las pacientes fueron genotipificadas mediante PCR-HRM, y se recolectaron antecedentes clínicos durante su embarazo. Se determinó que las proporciones de las frecuencias genotípicas y alélicas eran significativamente distintas entre ambos grupos, siendo el alelo de riesgo “A”, identificado en mayor proporción en el grupo de pacientes con DMG, observándose niveles de glicemia significativamente mayores. Finalmente, con los resultados obtenidos se logró establecer que el riesgo a desarrollar DMG era casi 7 veces mayor en pacientes que presentaban al menos un alelo de riesgo “A”. En conclusión, el alelo de riesgo “A” del SNP rs9939609 aumenta el riesgo de desarrollar DMG en mujeres embarazadas
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    Generación de un modelo clinico-genético durante el embarazo para la predicción temprana de glicemia alterada.
    (Universidad de Concepción, 2023) Ortega Contreras, Bernel Ignacio; Guzmán Gutiérrez, Enrique Alberto; Araya Quintana, Juan Andrés
    During pregnancy, blood glucose alteration causes a fetoplacental deregulation, increasing risk that both (the mother and her offspring) to suffer short- and long-term complications due to this condition. The diagnostic criteria currently used are late, there is not universal consensus or predictive methods that can early detect Altered Glycemia (AG) in this period. Several studies have shown that there are genetic and clinical factors that could be useful as predictors of AG during pregnancy. Within the genetics, variants have been found in the TCF7L2, FTO and DIO2 genes, which are related to an increased risk of developing this condition. The aim of this study was to generate a predictive model of AG in the second trimester of pregnancy, which included the genetic variants, clinical and biochemical data at the beginning of pregnancy. For this, clinical and biochemical information was collected from a sample of pregnant patients, who were classified according to their blood glucose levels (AG and normal glycemia (NG)), comparing both groups. These patients were genotyped according to the polymorphisms, to then establish the individual associations of each genotype with clinical and biochemical parameters of pregnant women. With this information and using the Soft independent modeling of class analogies (SIMCA) multivariate method, a predictive model of AG in the second trimester of pregnancy was generated, based on relevant clinical, biochemical, and genetic parameters of first trimester. In addition, through a regression analysis using Partial Least Squares (PLS), a predictive model of 2- hours post-load blood glucose in pregnancy was generated, using first trimester variables. Of the total pregnant patients (68), 35% (24) had AG during pregnancy, who were characterized by being older and presenting higher basal blood glucose levels in the first trimester of pregnancy. In the genetic analysis, no associations were found between the genetic variants and AG during pregnancy. However, for rs7903146 (TCF7L2) variant, the “TT” risk genotype was associated with higher weight and BMI in first trimester and elevated basal blood glucose levels in the second trimester of pregnancy, compared to the other genotypes. In addition, TSH levels were lower in patients with the risk allele "T". For the rs225014 (DIO2) variant, second trimester basal blood glucose levels were higher in carriers of the “CC” risk genotype, which was also associated with decreased total triiodothyronine (TT3) levels. Also, a positive correlation was established between the 2-hours post-load blood glucose levels and the genetic score, where the best model (R: 0.35) considered the rs12255372 (TCF7L2), rs9939609 (FTO) and rs225014 (DIO2) genotypes. In the multivariate analysis, the SIMCA predictive model for the classification of GA in pregnant women presented an AUC (Area under curve) for the ROC (receiver operating characteristic) curve of 0.8734, together with a sensitivity and specificity of 0.8182 and 0.9286 respectively, while PLS predictive model, for 2-hours post-load blood glucose levels at pregnancy, presented an AUC of 0.7890 with the highest sensitivity and specificity (0.7727 and 0.8333, respectively) at a glycemia cutoff of 115 mg/dL. Based on the presented results, the genetic factors together with the clinical and biochemical variables evaluated are relevant for the development of AG during pregnancy, and the predictive model would allow early detection of this condition.
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