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1.
J Endocr Soc ; 6(8): bvac092, 2022 Aug 01.
Artículo en Inglés | MEDLINE | ID: mdl-35854978

RESUMEN

Purpose: A study among Filipinos revealed that only 15% of patients with diabetes achieved glycemic control, and poor response to metformin could be one of the possible reasons. Recent studies demonstrate how genetic variations influence response to metformin. Hence, the present study aimed to determine genetic variants associated with poor response to metformin. Methods: Using a candidate variant approach, 195 adult Filipino participants with newly diagnosed type 2 diabetes mellitus (T2DM) were enrolled in a case-control study. Genomic DNA from blood samples were collected. Allelic and genotypic associations of variants with poor response to metformin were determined using exact statistical methods. Results: Several polymorphisms were nominally associated with poor response to metformin (P uncorr < 0.05). The most notable is the association of multiple variants in the SLC2A10 gene-rs2425911, rs3092412, and rs2425904-with common additive genetic mode of inheritance. Other variants that have possible associations with poor drug response include rs340874 (PROX-AS1), rs815815 (CALM2), rs1333049 (CDKN2B-AS1), rs2010963 (VEGFA), rs1535435 and rs9494266 (AHI1), rs11128347 (PDZRN3), rs1805081 (NPC1), and rs13266634 (SLC30A8). Conclusion: In Filipinos, a trend for the association for several variants was noted, with further observation that several mechanisms may be involved. The results may serve as pilot data for further validation of candidate variants for T2DM pharmacotherapy.

2.
Endocrinol Metab (Seoul) ; 32(4): 426-433, 2017 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-29199401

RESUMEN

BACKGROUND: Determining risk factors for diabetes insipidus (DI) after pituitary surgery is important in improving patient care. Our objective is to determine the factors associated with DI after pituitary surgery. METHODS: We reviewed records of patients who underwent pituitary surgery from 2011 to 2015 at Philippine General Hospital. Patients with preoperative DI were excluded. Multiple logistic regression analysis was performed and a predictive model was generated. The discrimination abilities of the predictive model and individual variables were assessed using the receiving operator characteristic curve. RESULTS: A total of 230 patients were included. The rate of postoperative DI was 27.8%. Percent change in serum Na (odds ratio [OR], 1.39; 95% confidence interval [CI], 1.15 to 1.69); preoperative serum Na (OR, 1.19; 95% CI, 1.02 to 1.40); and performance of craniotomy (OR, 5.48; 95% CI, 1.60 to 18.80) remained significantly associated with an increased incidence of postoperative DI, while percent change in urine specific gravity (USG) (OR, 0.53; 95% CI, 0.33 to 0.87) and meningioma on histopathology (OR, 0.05; 95% CI, 0.04 to 0.70) were significantly associated with a decreased incidence. The predictive model generated has good diagnostic accuracy in predicting postoperative DI with an area under curve of 0.83. CONCLUSION: Greater percent change in serum Na, preoperative serum Na, and performance of craniotomy significantly increased the likelihood of postoperative DI while percent change in USG and meningioma on histopathology were significantly associated with a decreased incidence. The predictive model can be used to generate a scoring system in estimating the risk of postoperative DI.

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