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Endocrine Abstracts (2018) 56 GP153 | DOI: 10.1530/endoabs.56.GP153

1Endocrinology Department, Hospital Universitari Arnau de Vilanova de Lleida. Grup de Recerca en Inmunologia i Metabolisme, Institut de Recerca Biomèdica de Lleida, Lleida, Spain; 2CIBER Diabetes y Enfermedades Metabólicas. ISCIII., Madrid, Spain; 3Endocrinology Department, Hospital Universitari Vall d’Hebron. Grup de Recerca en Diabetis i Metabolisme, Institut de Recerca Vall d’Hebron, Barcelona, Spain; 4Gendiag.exe, S.L, Barcelona, Spain; 5Endocrinology Department, Hospital Universitari de Bellvitge, Bellvitge, Spain; 6Endocrinology Department, Corporació Sanitària Parc Taulí, Sabadell, Spain; 7Bariatric Surgery Unit, Hospital Universitari Arnau de Vilanova, Lleida, Spain; 8Bariatric Surgery Unit, Hospital Universitari Vall d’Hebron, Barcelona, Spain; 9Bariatric Surgery Unit, Corporació Sanitària Parc Taulí, Sabadell, Spain.


Introduction: Obesity and its comorbidities, specially type 2 diabetes (T2D), are a major public health problem. The disappointing result of dietary treatment and the scarce of drugs have led to increased bariatric surgery (BS) as the most efficient therapeutic option. However, not all obese patients with T2D who undergo BS achieve diabetes remission.

Objective: To develop a genetic scoring system for predicting T2D remission following BS. 2) To compare our results with the current clinical based prediction score (DiaRem).

Material and methods: We used a retrospective Spanish cohort (n=820) that included 169 individuals with T2D followed at least 18 months after BS (109 gastric bypass and 60 sleeve gastrectomy). DNA was extracted from saliva samples and processed using Nutri inCode test (NiC, Ferrer inCode) based on 6 genetic predisposition risk scores (GPS). Each GPS consists of several SNPs which were shown to be implicated in appetite regulation, response to exercise, response to hypocaloric diet, response to lyfe style intervention, response to BS, and SNPs related to the presence of metabolic syndrome or T2D. Multivariate logistic regression was used for adding several GPS to DiaRem score creating new scores, to predicting the event of interest (T2D remission). The calibration of the adequacy of the different models was determined by Hosmer-Lemeshow test and the area under the receiver operating characteristic curve (AUC) was used for evaluating the prediction performance for each score.

Results: In patients underwent BS, the genetic test significantly predicted not only an excess weight loss higher than 50% [gastric bypass: 0.610 (0.503–0.717), P=0.044; sleeve gastrectomy: 0.693 (0.594–0.791), P<0.001)] but also T2D remission. In addition, this new test improved the AUC compared with DiaRem alone in patients underwent gastric bypass [0.816 (0.701–0.932) vs 0.718 (0.576–0.861), P=0.024] and sleeve gastrectomy gastrectomy [0.816 (95% IC: 0.701–0.932) vs 0.718 (0.576–0.861), P=0.024]. Notably the GPS for diabetes remision were not the same that for weight loss.

Conclusion: To identify subjects with an inadequate response before BS is a challenge for all healthcare systems. Our results suggest that genetic testing is a useful tool for this issue and could be incorporated to the current clinical practice. Clinical data helps to better predict diabetes remission following BS.

Aknowledgement: PERIS 2016 (SLT002/16/00497).

Volume 56

20th European Congress of Endocrinology

Barcelona, Spain
19 May 2018 - 22 May 2018

European Society of Endocrinology 

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